OpenfMRI has been deprecated. For new and up to date datasets please use openneuro.org.

Old dataset pages are available at legacy.openfmri.org.

Datasets

Project Name Investigators Accession Number Project Summary Sample Size Scanner Type License
Whole-brain background-suppressed pCASL MRI with 1D-accelerated 3D RARE Stack-Of-Spirals Readout- Dataset 2
  1. John A. Detre
  2. María A. Fernández-Seara
  3. Yulin V. Chang
  4. Ze Wang
  5. Marta Vidorreta
ds000235 <p>We investigated the use of accelerated 3D readouts to obtain whole-brain, high-SNR ASL perfusion maps and reduce SAR deposition. Parallel imaging was implemented along the partition-encoding direction in a pseudo-continuous ASL sequence with background-suppression and 3D RARE Stack-Of-Spirals readout, and its performance was evaluated in three small cohorts. First, both non-accelerated and two-fold accelerated single-shot versions of the sequence were evaluated in healthy volunteers during a motor-photic task, and the performance was compared in terms of temporal SNR, GM-WM contrast, and statistical significance of the detected activation. Secondly, single-shot 1D-accelerated imaging was compared to a two-shot accelerated version to assess benefits of SNR and spatial resolution for applications in which temporal resolution is not paramount. Third, the efficacy of this approach in clinical populations was assessed by applying the single-shot 1D-accelerated version to a larger cohort of elderly volunteers.</p> <p>&nbsp;</p> 4 3T Siemens Prisma D13D PDDL
Cross-language repetition priming
  1. Poldrack, R.A.
  2. Alvarez, R.
ds000051 <p>Native Spanish speakers who were proficient in English performed an abstract-concrete judgment with single Spanish or English words. &nbsp;Each item was repeated once, either in the same language or in the other language.</p> 13 Siemens Allegra PDDL
Classification learning and reversal
  1. Gluck, M.
  2. Myers, C.
  3. Creso Moyano, J.
  4. Shohamy, D.
  5. Pare-Blagoev, E. J.
  6. Clark, J.
  7. Poldrack, R.A.
ds000052 <p>Subjects performed two blocks of an event-related probabilistic classification learning task. They then performed two more blocks of the same task with the reward contingencies reversed.</p> 13 Siemens Allegra PDDL
Magnitude Effect
  1. Samuel M. McClure
  2. Jonathan D. Cohen
  3. Gökhan Aydogan
  4. Anthony Liatsis
  5. Bokyung Kim
  6. Ian C. Ballard
ds000223 <p>This is an fMRI study of the magnitude effect in intertemporal choice, which refers to the phenomenon that people become more patient as the magnitude of all of their options increases. We scanned participants in 2 blocked sessions each of low and high magnitude decisions. The study was conducted at two different sites with different scanners and data acquisition specifications.<br /> <br /> <a href="https://youtu.be/Rx8teThRGeM">Task Instruction video&nbsp;</a></p> <p><a href="https://youtu.be/OeNjEQ9kPgA">Task video&nbsp;</a></p> 19 Siemans Allegra 3T and GE Discovery 3T PDDL
Flavour Pleasantness (Oral Nutritional Supplements)
  1. Gert J. ter Horst
  2. L. Nanetti
  3. Remco J. Renken
  4. Liselore Weitkamp
  5. Jelle R. Dalenberg
ds000218 <p>Participants were randomly assigned to two experimental groups. The first group (n=23, mean age = 23.43, SD=2.33, range: 21&ndash;28) was recruited to taste 8 commercially available drinks (referred to as regular products) during a morning session. The second group (n=22, mean age = 24.67, SD=3.37, range: 21&ndash;33) was recruited to taste 6 ONS (oral nutritional supplements) products in the afternoon. These two groups were independent (i.e. no participant participated in both groups).<br /> Participants engaged in a tasting task containing 48 or 36 trials for the regular products and ONS group, respectively. During the course of the experiment, participants received visual cues and instructions in Dutch via a paradigm constructed in E-prime (Psychology Software Tools Inc., Pittsburgh). Every flavor stimulus was delivered 6 times balanced over all imaging runs and counterbalanced between participants. The paradigm was presented during four and three imaging runs, for the regular products and ONS group, respectively. Each imaging run lasted for approximately 15 minutes (depending on reaction times) and contained a series of 12 trials. During each trial, participants were warned for an upcoming taste delivery by an asterisk appearing centered on the screen (duration: 2s.). Subsequently, 2 ml of a taste stimulus was delivered in the mouth and participants were instructed to taste this stimulus with the cue &quot;Taste&quot; (in Dutch: &quot;Proeven&quot;, duration: 3.5s.). After tasting, participants were instructed to swallow the solution, cued as &quot;Swallow&quot; (in Dutch: &quot;Slikken&quot;, duration: 4s.), followed by a period in which they needed to passively &quot;Judge&quot; the taste (in Dutch: &quot;Beoordelen&quot;, duration: 22.5s.). We chose this long period to assure that BOLD responses associated with rating and tasting had minimal overlap. Finally, a 7-point Likert scale appeared on the screen, ranging from &quot;very unpleasant&quot; to &quot;very pleasant&quot;. Participants were instructed to express perceived pleasantness of the taste on the scale by using a button box held in their right hand. Every trial ended with a rinsing procedure, in which participants received a 2 ml bolus of a 5% artificial saliva solution (Saliva Orthana, TM) twice. The entire paradigm lasted for approximately 90 minutes, in which either 288 ml or 216 ml of liquid was consumed, for the regular products and ONS group, respectively. As baseline, we included four 15-second periods in each imaging run within both data sets, during which the participant was looking at a black screen with a red cross centered in the middle.<br /> MRI scans were performed using a 3-Tesla MR scanner (Philips Intera, Best, the Netherlands) equipped with a 32-channel head coil. A T1-weighted 3D fast field echo (FFE) whole brain image was obtained in transverse orientation for anatomical reference. Acquisition parameters: field of view (FOV) 256 &times; 232 &times; 170 mm3 (rl, ap, fh); voxel size 1 mm isotropic; TR = 9 ms; TE = 3.5 ms; flip angle 8&ordm;; SENSE factors: 2.5, 1 (ap, fh); 170 slices, scan duration = 246.3s. Functional brain images were acquired in sagittal orientation using the Principles of Echo-Shifting with a Train of Observations (PRESTO) sequence. Acquisition parameters: FOV 153 &times; 230 &times; 230 mm3 (rl, ap, fh); voxel size 2.87 &times; 2.87 &times; 3 mm3; TR = 20 ms; TE = 30 ms; flip angle 7&ordm;; SENSE factors: 1.9, 1.9 (rl, ap); scan time per volume 1.532s. As the experiment was self-paced, the number of volumes per imaging run ranged between 580 and 600.<br /> Due to technical difficulties with the gustometer or scanner, data was missing for several trials. We removed participants missing more than 25% of their data (3 ONS group, 1 regular drinks group). Furthermore, 1 participant in the regular drinks group was removed due to a brain abnormality. Therefore, fMRI analysis was performed on data from 19 and 21 participants for the ONS and regular drinks groups, respectively.<br /> We experienced technical difficulties with the PRESTO sequence. As a result, several PRESTO images were missing at the start of imaging runs for 10 participants (on average 0.054% per data set).</p> <p>NOTE: This study has two datasets asscoiated with it. One for ONS products(ds000218) and other for RP products (ds000219)</p> <p>The paradigm is similar to http://www.sciencedirect.com/science/article/pii/S1053811915005674 but with some adjustments.</p> 19 Philips Intera 3T PDDL
The Midnight Scan Club (MSC) dataset
  1. Nico U.F. Dosenbach
  2. Steven M. Nelson
  3. Steven E. Petersen
  4. Bradley L. Schlaggar
  5. Abraham Z. Snyder
  6. Joshua S. Shimony
  7. Kathleen B. McDermott
  8. Annie Nguyen
  9. Rebecca S. Coalson
  10. Jacqueline M. Hampton
  11. Haoxin Sun
  12. Caterina Gratton
  13. Catherine Hoyt-Drazen
  14. Mario Ortega
  15. Jeffrey J. Berg
  16. Deanna J. Greene
  17. Dillan J. Newbold
  18. Adrian W. Gilmore
  19. Timothy O. Laumann
  20. Evan M. Gordon
ds000224 <div> <div> <div>The goal of the MSC project is to enable precise MRI-based characterization of individual humans by collecting large quantities of MRI and fMRI data on each of ten subjects. In each subject, we collected five hours of resting state fMRI, six hours of task fMRI across four different tasks, and four scans in each of four different anatomical modalities--T1, T2, MRA, and MRV. This dataset includes all raw data in all ten subjects. In addition, we have included hand-edited T1-derived cortical surfaces, fully preprocessed volumetric and surface-based resting-state data, and individualized cortical parcellations and large-scale networks derived from the resting-state data.</div> </div> </div> 10 Siemens 3.0T Tim Trio, software version syngo MR B17 PDDL
Imaging [18F]AV-1451 and [18F]AV-45 in acute and chronic traumatic brain injury
  1. Sam Gandy
  2. Patrick R. Hof
  3. Mary Sano
  4. Robert C. Cantu
  5. James R. Stone
  6. Steven T. DeKosky
  7. Cheuk Y. Tang
  8. Edmund Wong
  9. Bradley N. Delman
  10. Kristen Dams-O’Connor
  11. Wayne Gordon
  12. Barry Jordan
  13. Laili Soleimani
  14. Karin Knesaurek
  15. Lale Kostakoglu
  16. Jennifer A. Short
  17. Corey Fernandez
  18. Mariel Y. Pullman
  19. Dara Dickstein
ds000204 <p>The potential long-term effects of Traumatic Brain Injury (TBI) are poorly understood. Repeated concussions have been associated with an elevated incidence of Alzheimer&rsquo;s disease (AD) as well as chronic traumatic encephalopathy (CTE). There are growing concerns about the long-term neurologic consequences of head impact exposure from routine participation in contact sports (e.g., boxing, football). Brain autopsies of athletes with confirmed CTE have demonstrated tau-immunoreactive neurofibrillary tangles and neuropil threads (known as tauopathy). The relationship between exposure to repetitive head impact and the subsequent development of chronic neurodegenerative disease has not been established. Further, as the diagnosis of CTE (defined by the presence of tauopathy) is presently made at autopsy, clinical tools and biomarkers for detecting it remain to be defined. We aim to determine whether these individuals are on the same trajectory of neurodegenerative disease seen in AD or in CTE. Our study will utilize both [18F]-AV-1451 and [18F]-T807 PET imaging to investigate amyloid and tau accumulation in subjects with a history of concussions. We will obtain MRI, PET, and neurocognitive data in a cohort of 25 subjects with a history of TBIs and a cohort of 25 controls. This dataset currently contains data acquired from two sessions (3.9 years apart)&nbsp;from&nbsp;a single subject, including two T1w scans and two PET scans.</p> 1 Siemens PDDL
Affective Videos
  1. Douglas H. Wedell
  2. Svetlana V. Shinkareva
  3. Jing Wang
  4. Jongwan Kim
ds000205 <p>The goal of this study was to determine whether affective states can be similarly identified when participants view dynamic naturalistic audiovisual stimuli. Eleven participants viewed 5s audiovisual clips in a passive viewing task in the scanner. Valence and arousal for individual trials were identified both within and across participants based on distributed patterns of activity in areas selectively responsive to audiovisual naturalistic stimuli while controlling for lower level features of the stimuli. In addition, the brain regions identified by searchlight analyses to represent valence and arousal were consistent with previously identified regions associated with emotion processing.</p> 11 Siemens Magnetom Trio 3.0T whole-body scanner (Siemens, Erlangen, Germany) PDDL
Brain connectivity predicts placebo response across chronic pain clinical trials
  1. Marwan N. Baliki
  2. A. Vania Apkarian
  3. Thomas J. Schnitzer
  4. Etienne Vachon-Presseau
  5. Ali Mansour
  6. Pascal Tétreault
ds000208 <p>Placebo response is extensively studied in healthy subjects and for experimental manipulations. However, in the clinical setting it has been primarily relegated to statistical confounds. Here, for the first time we examine predictability of future placebo response in the clinical setting in patients with chronic osteoarthritis pain. We examine resting state fMRI brain connectivity prior to start of clinical trial, and in the setting of neutral instructions regarding treatment. Our results show that clinical placebo pill ingestion shows stronger analgesia than no treatment, is predictable from resting state BOLD fMRI, and right mid-frontal gyrus degree count (extent of functional connectivity) identifies placebo pill responders in one trial and can be validated (95% correct) in the placebo group of a second trial but not in the active drug treatment (duloxetine) group. By modeling the expected placebo response in subjects receiving active drug treatment, we uncover a placebo-corrected drug response predictive brain signal, and show that in some subjects active drug tends to enhance, while in others interferes, with predicted placebo response. Together, these results provide evidence for clinical placebo being predetermined by brain biology, and show that brain imaging may also identify a placebo-corrected prediction of response to active treatment.</p> 76 3T Siemens Trio whole-body scanner with echo-planar imaging (EPI) capability PDDL
The human Voice Areas: spatial organisation and inter-individual variability in temporal and extra-temporal cortices
  1. Fleming, D
  2. Watson, RH
  3. Bestelmeyer, PEG
  4. Charest, I
  5. Latinus, M
  6. Valdes-Sosa, M
  7. Gorgolewski, KJ
  8. McAleer, P
  9. Belin, P
  10. Pernet, CR
ds000158 <p>FMRI studies increasingly examine functions and properties of non-primary areas of human auditory cortex. However there is currently no standardized localization procedure to reliably identify specific areas across individuals such as the standard &#39;localizers&#39; available in the visual domain. Here we present an fMRI &#39;voice localizer&#39; scan allowing rapid and reliable localization of the voice-sensitive &#39;temporal voice areas&#39; (TVA) of human auditory cortex. We describe results obtained using this standardized localizer scan in a large cohort of normal adult subjects. Most participants (94%) showed bilateral patches of significantly greater response to vocal than non-vocal sounds along the superior temporal sulcus/gyrus (STS/STG). Individual activation patterns, although reproducible, showed high inter-individual variability in precise anatomical location. Cluster analysis of individual peaks from the large cohort highlighted three bilateral clusters of voice-sensitivity, or &quot;voice patches&quot; along posterior (TVAp), mid (TVAm) and anterior (TVAa) STS/STG, respectively. A series of extra-temporal areas including bilateral inferior prefrontal cortex and amygdalae showed small, but reliable voice sensitivity as part of a large-scale cerebral voice network. Stimuli for the voice localizer scan and probabilistic maps in MNI space are available for download.</p> 218 Siemens Tim Trio 3T CC-BY 4.0
Word and object processing
  1. Devlin, J.
  2. Knierim, I.
  3. Pattamadilok, C.
  4. Duncan, K.
ds000107 <p>Subjects performed a&nbsp;visual one-back with four categories of items: written words, objects, scrambled objects and consonant letter strings.</p> 49 Siemens 1.5T PDDL
Incidental encoding task (Posner Cueing Paradigm)
  1. Anthony D. Wagner
  2. J. Benjamin Hutchinson
  3. Melina R. Uncapher
ds000110 <p>Subjects were scanned while incidentally encoding a series of visually presented real objects and greebles (meaningless objects) in a variant of the Posner cueing paradigm. Subjects covertly shifted their attention to the left or right of fixation, as cued by a centrally-presented arrow prior to item onset, and made a real object versus greeble judgment about the stimulus appearing in the cued or uncued location. Items appeared in the uncued location with a probability of .18. Subjects performed an unscanned memory test following encoding, in which they indicated their memory for old and new real objects using the following four responses: high confident old, low confident old, low confident new, high confident new. For trials in which subjects responded with one of the two old responses, a source memory judgment about the location (left or right side of the screen) of the object at study followed the recognition judgment.</p> 18 3 T Signa MR scanner PDDL
False belief task
  1. Jason P. Mitchell
  2. Eshin Jolly
  3. Joseph M. Moran
ds000109 <p>Participants read stories and answered questions that referred to either a person&#39;s false belief (mental trials) or to outdated physical representations, such as an old photograph (physical trials). Participants saw twelve stories of each type across two functional runs.</p> 33 3T Tim Trio MRI scanner (Siemens). PDDL
Maclaren test-retest brain volume dataset
  1. Roland Bammer
  2. Nancy Fischbein
  3. Sjoerd B. Vos
  4. Zhaoying Han
  5. Julian Maclaren
ds000239 <p>Retest T1-weighted images from 3 participants, each scanned 40 times.</p> 3 GE MR750, DV22.0_V02_1122.a, XRMB gradient set PDDL
A multimodal brain imaging dataset on sleep deprivation in young and old humans: The Sleepy Brain Project I
  1. Torbjörn Åkerstedt
  2. Mats Lekander
  3. Håkan Fischer
  4. Göran Kecklund
  5. Peter Fransson
  6. Predrag Petrovic
  7. John Axelsson
  8. Tina Sundelin
  9. Kristoffer NT Månsson
  10. Jia Jia Liu
  11. Catharina Lavebratt
  12. Johanna Schwarz
  13. Hanna Å Thuné
  14. Paolo d’Onofrio
  15. Sandra Tamm
  16. Gustav Nilsonne
ds000201 <h4>Dataset Information</h4> <p>The Stockholm Sleepy Brain Study I is a functional brain imaging study where 48 younger (20-30 years) and 36 older (65-75 years) healthy participants underwent magnetic resonance imaging after normal sleep and partial sleep deprivation in a crossover design. We performed three experiments investigating emotional mimicry, empathy for pain, and cognitive reappraisal, as well as resting state functional magnetic resonance imaging (fMRI). We also acquired T1- and T2-weighted structural images and diffusion tensor images. On the night before imaging, participants were monitored with ambulatory polysomnography and were instructed to sleep either as usual or only three hours. Participants came to the scanner the following evening. Besides MRI scanning, participants underwent behavioral tests and contributed blood samples, which have been stored in a biobank and used for DNA analyses. Participants also completed a variety of self-report measures. The resulting multimodal dataset may be useful for hypothesis generation or independent validation of effects of sleep deprivation and aging, as well as investigation of cross-sectional associations between our different outcomes.</p> <h4>Dataset Notes</h4> <p><strong>The faces and arrows task-based fMRI experiment data will be published at a later time.</strong></p> <p><strong>Raw polysomnography&nbsp;data are&nbsp;available upon request.​</strong></p> <p>The currently published data set includes:</p> <p>Hands task-based fMRI data</p> <p>Resting state fMRI data</p> <p>Demographics, surveys, questionnaire data</p> <p>Eye tracking data</p> <p>High resolution T1-weighted and T2-weighted structural scans</p> <p>B0 field map data</p> <p>Diffusion-weighted imaging scans</p> <p>DNA analysis results</p> <p><strong>Data Descriptor Manuscript</strong></p> <p>A preprint of the corresponding <a href="https://openarchive.ki.se/xmlui/handle/10616/45181" target="_blank">data descriptor manuscript</a> (submitted) is available at the Karolinska Institutet open archive.</p> 84 GE Discovery 3T PDDL
Maturational Changes in Anterior Cingulate and Frontoparietal Recruitment Support the Development of Error Processing and Inhibitory Control (Antistate)
  1. B. Luna
  2. M. E. Wheeler
  3. Velanova, K.
ds000119 <p>Documenting the development of the functional anatomy underlying error processing is critically important for understanding age-related improvements in cognitive performance. Here we used functional magnetic resonance imaging to examine time courses of brain activity in 73&nbsp;individuals aged 8&ndash;27 years during correct and incorrect performance of an oculomotor task requiring inhibitory control. Canonical eye-movement regions showed increased activity for correct versus error trials but no differences between children, adolescents and young adults, suggesting that core task processes are in place early in development. Anterior cingulate cortex (ACC) was a central focus. In rostral ACC all age groups showed significant deactivation during correct but not error trials, consistent with the proposal that such deactivation reflects suspension of a &ldquo;default mode&rdquo; necessary for effective controlled performance. In contrast, dorsal ACC showed increased and extended modulation for error versus correct trials in adults, which, in children and adolescents, was significantly attenuated. Further, younger age groups showed reduced activity in posterior attentional regions, relying instead on increased recruitment of regions within prefrontal cortex. This work suggests that functional changes in dorsal ACC associated with error regulation and error-feedback utilization, coupled with changes in the recruitment of &ldquo;long-range&rdquo; attentional networks, underlie age-related improvements in performance.</p> 73 3T Siemens Allegra MRI scanner PDDL
Value generalization in human avoidance learning
  1. Ben Seymour
  2. Agnes Norbury
ds000249 <p>Generalization during aversive decision-making allows us to avoid a broad range of potential threats following experience with a limited set of exemplars. However, over-generalization, resulting in excessive and inappropriate avoidance, has been implicated in a variety of psychological disorders. Here, we use reinforcement learning modelling to dissect out different contributions to the generalization of instrumental avoidance in two groups of human volunteers (N=26, N=482). We found that generalization of avoidance could be parsed into perceptual and value-based processes, and further, that value-based generalization could be subdivided into that relating to aversive and neutral feedback &mdash; with corresponding circuits including primary sensory cortex, anterior insula, and ventromedial prefrontal cortex, respectively. Further, generalization from aversive, but not neutral, feedback was associated with self-reported anxiety and intrusive thoughts. These results reveal a set of distinct mechanisms that mediate generalization in avoidance learning, and show how specific individual differences within them can yield anxiety.</p> 26 Siemens Magnetom Skyra Fit (3T) PDDL
Working memory in healthy and schizophrenic individuals
  1. Csernansky JG
  2. Repovs G
  3. Barch DM
ds000115 <p>Individuals diagnosed with schizophrenia, their unaffected siblings, and healthy controls performed three levels of an n-back task (0, 1, and 2-back).</p> <p><strong>Warning: The events files in this dataset do not seem to be correct. We cannot guarantee their accuracy and thus recommend that you disregard them entirely.</strong></p> 99 3T Siemens Trio PDDL
Flavour Pleasantness (Regular Products)
  1. Gert J. ter Horst
  2. L. Nanetti
  3. Remco J. Renken
  4. Liselore Weitkamp
  5. Jelle R. Dalenberg
ds000219 <p>Participants were randomly assigned to two experimental groups. The first group (n=23, mean age = 23.43, SD=2.33, range: 21&ndash;28) was recruited to taste 8 commercially available drinks (referred to as regular products) during a morning session. The second group (n=22, mean age = 24.67, SD=3.37, range: 21&ndash;33) was recruited to taste 6 ONS (oral nutritional supplements) products in the afternoon. These two groups were independent (i.e. no participant participated in both groups).<br /> Participants engaged in a tasting task containing 48 or 36 trials for the regular products and ONS group, respectively. During the course of the experiment, participants received visual cues and instructions in Dutch via a paradigm constructed in E-prime (Psychology Software Tools Inc., Pittsburgh). Every flavor stimulus was delivered 6 times balanced over all imaging runs and counterbalanced between participants. The paradigm was presented during four and three imaging runs, for the regular products and ONS group, respectively. Each imaging run lasted for approximately 15 minutes (depending on reaction times) and contained a series of 12 trials. During each trial, participants were warned for an upcoming taste delivery by an asterisk appearing centered on the screen (duration: 2s.). Subsequently, 2 ml of a taste stimulus was delivered in the mouth and participants were instructed to taste this stimulus with the cue &quot;Taste&quot; (in Dutch: &quot;Proeven&quot;, duration: 3.5s.). After tasting, participants were instructed to swallow the solution, cued as &quot;Swallow&quot; (in Dutch: &quot;Slikken&quot;, duration: 4s.), followed by a period in which they needed to passively &quot;Judge&quot; the taste (in Dutch: &quot;Beoordelen&quot;, duration: 22.5s.). We chose this long period to assure that BOLD responses associated with rating and tasting had minimal overlap. Finally, a 7-point Likert scale appeared on the screen, ranging from &quot;very unpleasant&quot; to &quot;very pleasant&quot;. Participants were instructed to express perceived pleasantness of the taste on the scale by using a button box held in their right hand. Every trial ended with a rinsing procedure, in which participants received a 2 ml bolus of a 5% artificial saliva solution (Saliva Orthana, TM) twice. The entire paradigm lasted for approximately 90 minutes, in which either 288 ml or 216 ml of liquid was consumed, for the regular products and ONS group, respectively. As baseline, we included four 15-second periods in each imaging run within both data sets, during which the participant was looking at a black screen with a red cross centered in the middle.<br /> MRI scans were performed using a 3-Tesla MR scanner (Philips Intera, Best, the Netherlands) equipped with a 32-channel head coil. A T1-weighted 3D fast field echo (FFE) whole brain image was obtained in transverse orientation for anatomical reference. Acquisition parameters: field of view (FOV) 256 &times; 232 &times; 170 mm3 (rl, ap, fh); voxel size 1 mm isotropic; TR = 9 ms; TE = 3.5 ms; flip angle 8&ordm;; SENSE factors: 2.5, 1 (ap, fh); 170 slices, scan duration = 246.3s. Functional brain images were acquired in sagittal orientation using the Principles of Echo-Shifting with a Train of Observations (PRESTO) sequence. Acquisition parameters: FOV 153 &times; 230 &times; 230 mm3 (rl, ap, fh); voxel size 2.87 &times; 2.87 &times; 3 mm3; TR = 20 ms; TE = 30 ms; flip angle 7&ordm;; SENSE factors: 1.9, 1.9 (rl, ap); scan time per volume 1.532s. As the experiment was self-paced, the number of volumes per imaging run ranged between 580 and 600.<br /> Due to technical difficulties with the gustometer or scanner, data was missing for several trials. We removed participants missing more than 25% of their data (3 ONS group, 1 regular drinks group). Furthermore, 1 participant in the regular drinks group was removed due to a brain abnormality. Therefore, fMRI analysis was performed on data from 19 and 21 participants for the ONS and regular drinks groups, respectively.<br /> We experienced technical difficulties with the PRESTO sequence. As a result, several PRESTO images were missing at the start of imaging runs for 10 participants (on average 0.054% per data set).</p> <p>NOTE: This study has two datasets asscoiated with it. One for ONS products(ds000218) and other for RP products (ds000219)</p> <p>The paradigm is similar to http://www.sciencedirect.com/science/article/pii/S1053811915005674 but with some adjustments.</p> 21 Philips Intera 3T PDDL
Classification learning and tone-counting
  1. Poldrack, R.A.
  2. Knowlton, B.J.
  3. Foerde, K.
ds000011 <p>Fourteen participants were trained on two different classification problems while they were scanned by using fMRI. Participants were trained on one problem under single-task (ST) conditions and on the other problem while performing a concurrent tone-counting task. During training, subjects learned the categories based on trial-by-trial feedback. After training, subjects received an additional block of probe trials using a mixed event-related (ER) fMRI paradigm, during which they classified items that had been trained under either ST or dual-task (DT) conditions. To&nbsp;measure how well participants had learned under each condition, no feedback was presented during the probe block, and all items were presented under ST conditions. &nbsp;An additional tone-counting localizer scan presented blocks of the tone counting task (followed by a probe at the end of each block) compared to rest.</p> 14 3T Siemens Allegra head-only MR scanner PDDL
Multi-echo fMRI replication sample of autobiographical memory, prospection and theory of mind reasoning tasks
  1. R. Nathan Spreng
  2. Wen-Ming Luh
  3. Elizabeth DuPre
ds000210 <p>We collected a replication sample of Spreng and Grady (J Cogn. Neurosci. 22, 1112-1123, 2010). Here we provide the resulting dataset of multi-echo fMRI data in 31 young adults during autobiographical remembering, imagining, and mentalizing; we also provide an additional resting-state scan for each subject.</p> 31 GE Discovery MR750 3.0T PDDL
Washington University 120
  1. Jonathan Power
  2. Brad Schlaggar
  3. Steve Petersen
ds000243 <p>These 120 MRI datasets are being released to the public along as part of the materials for &ldquo;Temporal interpolation alters motion in fMRI scans: magnitudes and consequences for artifact detection&rdquo; by Power et al. in PLOS ONE.</p> <p>Included for each subject is a T1-weighted anatomical image (MP-RAGE) and one or more T2*-weighted scans (resting state BOLD scans)</p> <p>All subjects&nbsp;<br /> &nbsp;&nbsp; &nbsp;- were &ldquo;typical&rdquo; young adults that reported no significant neurological or psychiatric history<br /> &nbsp;&nbsp; &nbsp;- were right-handed and reported that English was their first language<br /> &nbsp;&nbsp; &nbsp;- were scanned at Washington University in Saint Louis on a Siemens MAGNETOM Tim Trio 3T scanner with a Siemens 12-channel head coil<br /> &nbsp;&nbsp; &nbsp;- were scanned using interleaved ascending product sequences for T2* data<br /> &nbsp;&nbsp; &nbsp;- were scanned in the eyes-open resting state fixating a white crosshair on a black background</p> <p>The data have been described in multiple publications from the Petersen/Schlaggar group,<br /> &nbsp;&nbsp; &nbsp;- beginning with Power et al., 2013 &ldquo;Evidence for hubs in human brain networks&rdquo; in Neuron<br /> &nbsp;&nbsp; &nbsp;- and most comprehensively in Power et al., 2014 &ldquo;Methods to detect, characterize, and remove motion artifact in resting state fMRI&rdquo; in Neuroimage<br /> &nbsp;&nbsp; &nbsp;- as well as several other publications<br /> &nbsp; &nbsp;&nbsp;</p> <p><br /> &nbsp;</p> 120 Siemens MAGNETOM Tim Trio 3T PDDL
Whole-brain background-suppressed pCASL MRI with 1D-accelerated 3D RARE Stack-Of-Spirals Readout- Dataset 3
  1. John A. Detre
  2. María A. Fernández-Seara
  3. Yulin V. Chang
  4. Ze Wang
  5. Marta Vidorreta
ds000236 <p>We investigated the use of accelerated 3D readouts to obtain whole-brain, high-SNR ASL perfusion maps and reduce SAR deposition. Parallel imaging was implemented along the partition-encoding direction in a pseudo-continuous ASL sequence with background-suppression and 3D RARE Stack-Of-Spirals readout, and its performance was evaluated in three small cohorts. First, both non-accelerated and two-fold accelerated single-shot versions of the sequence were evaluated in healthy volunteers during a motor-photic task, and the performance was compared in terms of temporal SNR, GM-WM contrast, and statistical significance of the detected activation. Secondly, single-shot 1D-accelerated imaging was compared to a two-shot accelerated version to assess benefits of SNR and spatial resolution for applications in which temporal resolution is not paramount. Third, the efficacy of this approach in clinical populations was assessed by applying the single-shot 1D-accelerated version to a larger cohort of elderly volunteers.</p> 18 3T Siemens Prisma PDDL
Pre-adolescents Exposure to Manganese
  1. Emilia Iannilli
ds000200 <p>The data included in this pilot study are a collection of 14 pre-adolescents recruited in one of the Italian sites exposed to Manganese. The mean age of the two groups was respectively 14.7 years (s.d.=2.4) and 14.6 years (s.d.= 0.5) with 4 girls in the first group and 2 in the second.</p> <p>The fMRI paradigm included an olfactory stimulation which consisted of 12 alternating task-rest blocks of 25 seconds, 10 volumes/block (120 volumes) for a total acquisition time of 5 minutes. The MRI acquisition protocol included a Coronal T2 FSE (TR/TE&nbsp; 5000/102 slice thickness 2 mm, no gap) use for the volumetric measurement of the olfactory bulb; a time series of 2D echo planar imaging (EPI) (TR/TE 2500/50 ms,&nbsp; 28 axial slices, 3.3 mm thickness, 1.1 mm inter-slice gap, matrix size&nbsp; 64x64).</p> <p><strong>Note: Please see <a href="https://openfmri.org/dataset/ds000220/">https://openfmri.org/dataset/ds000220/</a> if you are looking for data associated with the following paper: Roy&nbsp;A, Bernier&nbsp;RA, Wang&nbsp;J, Benson&nbsp;M, French&nbsp;JJ&nbsp;Jr, et al. (2017) The evolution of cost-efficiency in neural networks during recovery from traumatic brain injury. PLOS ONE 12(4): e0170541. <a href="https://doi.org/10.1371/journal.pone.0170541">https://doi.org/10.1371/journal.pone.0170541</a></strong></p> 14 1.5T Aera, Siemens, Erlangen, Germany PDDL
A multi-subject, multi-modal human neuroimaging dataset
  1. Henson, RN
  2. Wakeman, DG
ds000117 <p>This dataset contains data acquired with multiple functional and structural neuroimaging modalities on the same nineteen healthy volunteers. The functional data include Electroencephalography (EEG), Magnetoencephalography (MEG) and functional Magnetic Resonance Imaging (fMRI) data, recorded while the volunteers performed multiple runs of hundreds of trials of a simple perceptual task on pictures of familiar, unfamiliar and scrambled faces during two visits to the laboratory. The structural data include T1-weighted MPRAGE, Multi-Echo FLASH and Diffusion-weighted MR sequences. Though only from a small sample of volunteers, these data can be used to develop methods for integrating multiple modalities from multiple runs on multiple participants, with the aim of increasing the spatial and temporal resolution above that of any one modality alone. They can also be used to integrate measures of functional and structural connectivity, and as a benchmark dataset to compare results across the many neuroimaging analysis packages.</p> 19 Siemens 3T TIM TRIO Creative Commons Attribution 4.0 International Public License
DWI Traveling Human Phantom Study
  1. Laura A. Flashma
  2. Elizabeth Aylward
  3. Mark J. Lowe
  4. Sarah Reading
  5. Jessica A. Turner
  6. Karl G. Helmer
  7. Susumu Mori
  8. Kelvin Lim
  9. Bryon A. Mueller
  10. Bradley D. Bolster Jr.
  11. Jeffrey D. Long
  12. Hans J. Johnson
  13. Dawei Liu
  14. Joy T. Matsui
  15. Vincent A. Magnotta
ds000206 <p>A number of studies are now collecting diffusion tensor imaging (DTI) data across sites. While the reliability of anatomical images has been established by a number of groups, the reliability of DTI data has not been studied as extensively. In this study, five healthy controls were recruited and imaged at eight imaging centers. Repeated measures were obtained across two imaging protocols allowing intra-subject and inter-site variability to be assessed. Regional measures within white matter were obtained for standard rotationally invariant measures: fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity. Intra-subject coefficient of variation (CV) was typically &lt;1% for all scalars and regions. Inter-site CV increased to *1%&ndash;3%. Inter-vendor variation was similar to inter-site variability. This variability includes differences in the actual implementation of the sequence.</p> 5 Siemens 3T TIM Trio, Philips 3T Achieva PDDL
MyConnectome
  1. Laumann, T
  2. Poldrack, R
ds000031 <p>This dataset contains the MRI data from the MyConnectome study.&nbsp; The data are broken into several parts:</p> <p>Sessions 14-104 are from the original acquisition period of the study performed at the University of Texas using a Siemens Skyra 3T scanner. &nbsp;All resting data were collected with eyes closed.</p> <p>Session 105 is a follow-up session performed at Washington University using a Siemens Trio 3T scanner in which data were collected manipulating eyes open/closed across sessions.</p> <p>Session 106 is a follow-up session performed at Stanford University using a GE MR750 3T scanner, in which a high angular resolution diffusion imaging acquisition was performed.</p> <div> <div>&nbsp;</div> <div>We request that researchers who discover any health-relevant findings will contact Dr. Poldrack (poldrack at gmail dot com) prior to publicly releasing those results.</div> </div> 1 Siemens Skyra 3T PDDL
Trial timing for multivariate pattern analysis
  1. Adke A
  2. De Araujo Sanchez M A
  3. Zeithamova D
ds000238 <p>This data was collected to investigate experimental design optimization for pattern-information approaches to fMRI data analysis. Participants were scanned while encoding images of animals and tools. There were 5 different stimulus presentation designs, and each participant completed to runs under each design. The designs varied in the number of trials and trial timing within fixed duration scans. Trial timing conditions with fixed onset-to-onset timing ranged from slow 12-s trials with two repetitions of each item to quick 6-s trials with four repetitions per item. We also tested a jittered version of the quick design with 4&ndash;8 s trials. After the scans, participants completed a memory test.</p> 35 Siemens MAGNETOM Skyra PDDL
MPI-Leipzig_Mind-Brain-Body
  1. Daniel S. Margulies
  2. Jonathan Smallwood
  3. Jared Pool
  4. Anastasia Osoianu
  5. Katharina Ohrnberger
  6. Yelyzaveta Kramarenko
  7. Rebecca Jost
  8. Philipp Haueis
  9. Krzysztof J. Gorgolewski
  10. Laura Golz
  11. Nicolas Farrugia
  12. Haakon Engen
  13. Maria Dreyer
  14. Roberto Cozatl
  15. Blazej M. Baczkowski
  16. Sarah Krause
  17. Marcel Falkiewicz
  18. Julia M. Huntenburg
  19. Johannes Golchert
  20. Mark E. Lauckner
  21. Sabine Oligschläger
  22. Natacha Mendes
  23. Deniz Kumral
  24. Janis Reichelt
  25. Andrea Reiter
  26. Miray Erbey
  27. Josefin Röbbig
  28. Lina Schaare
  29. Michael Gaebler
  30. Anahit Babayan
  31. Arno Villringer
ds000221 <p>The participants included in this dataset participated in one or two protocols. Each of these protocols included structural and resting-state fMRI data acquisition, as well as an extensive battery of behavioural tests.</p> 320 Siemens Verio 3T PDDL
MEG-BIDS OMEGA sample
  1. Sylvain Baillet
  2. François Tadel
  3. Jeremy Moreau
  4. Elizabeth Bock
  5. Guiomar Niso
ds000247 <p>This dataset is a subset from the OMEGA (Open MEG Archives) free and open data repository for MEG data (Niso et al. 2015). The present sample has been organized according to the specifications of MEG-BIDS to obtain feedback from the user community.</p> <p>Niso G., Rogers C., Moreau J.T., Chen L.Y., Madjar C., Das S., Bock E., Tadel F., Evans A.C., Jolicoeur P., Baillet S. (2015). OMEGA: The Open MEG Archive. NeuroImage 124, 1182-1187. doi:10.1016/j.neuroimage.2015.04.028</p> 5 MEG, CTF Inc. 275 channels CC0
MNE Sample Data
  1. Alexandre Gramfort
  2. Matti S Hämäläinen
ds000248 <div> <p><br /> This dataset has been acquired for educational purposes. It contains simultaneous MEG/EEG data. For many years it has been used to train MNE users and to serve as illustration in the tutorials of the MNE software. The present dataset has been organized according to the specifications of MEG-BIDS to facilitate future data analysis.</p> </div> 1 Elekta Vectorview CC0
Block design food and nonfood picture viewing task
  1. D. T. D. de Ridder
  2. Catherine Evers
  3. Floor M. Kroese
  4. Paul A. M. Smeets
ds000157 <p>Thirty female subjects performed a passive viewing task with blocks of food and nonfood images. More procedures can be found in the publication&quot;&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/23578759" target="_blank"><em>Allured or alarmed: counteractive control responses to food temptations in the brain</em>.</a>&nbsp;</p> <p>&quot;During scanning, subjects alternately viewed 24&nbsp;s blocks of palatable food images (8 blocks) and non-food images (i.e., office utensils; 8 blocks), interspersed with 8&ndash;16&nbsp;s rest blocks showing a crosshair (12&nbsp;s on average). Halfway the task there was a 10&nbsp;s break. In the image blocks, 8 images were presented for 2.5&nbsp;s each with a 0.5&nbsp;s inter-stimulus interval. All pictures were of equal size and displayed the (food) object on a white background. Food pictures were selected to represent foods that are both attractive and &lsquo;forbidden&rsquo; (i.e., fattening), congruent with our definition of temptations.&quot;</p> <p><strong>Dataset Contains</strong>: BOLD-contrast fMRI data and&nbsp;T1-weighted high resolution structural scans</p> 30 Philips Achieva 3 Tesla PDDL
Cost Analysis TBI
  1. Frank Hillary
  2. Arnab Roy
ds000220 <p>Resting state connectivity and graph theory at 3 time points during recovery after traumatic brain injury</p> 14 3T Siemens, 3T Philips PDDL
UCLA Consortium for Neuropsychiatric Phenomics LA5c Study
  1. Sabb, F
  2. Karlsgodt, K
  3. Congdon, E
  4. Freimer, N
  5. London, E
  6. Cannon, T
  7. Poldrack, R
  8. Bilder, R
ds000030 <p>The Consortium for Neuropsychiatric Phenomics (CNP) is a large study funded by the NIH Roadmap Initiative that aims to&nbsp;facilitate discovery of the genetic and environmental bases of variation in psychological and neural system phenotypes, to elucidate the mechanisms that link the human genome to complex psychological syndromes, and to foster breakthroughs in the development of novel treatments for neuropsychiatric disorders.</p> <p>The study includes imaging of a large group of healthy individuals from the community (138&nbsp;subjects), as well as samples of individuals diagnosed with schizoprenia (58), bipolar disorder (49), and ADHD (45).</p> <p>The participants, ages 21-50, were recruited by community advertisements from the Los Angeles area and completed extensive neuropsychogical testing, in addition to fMRI scanning. To be included individuals had to be either &quot;White, Not of Hispanic or Latino Origin&quot; or &quot;Hispanic or Latino, of Any Race&quot; following NIH designations of racial and ethnic minority groups, and have completed at least 8 years of education (other racial and ethnic minority groups were excluded because this was thought to increase risk of confounding planned genetic studies). For participants who spoke both English and Spanish, language for testing was determined by a verbal fluency test. Participants were screened for neurological disease, history of head injury with loss of consciousness or cognitive sequelae, use of psychoactive medications, substance dependence within past 6 months, history of major mental illness or ADHD, and current mood or anxiety disorder. Self-reported history of psychopathology was verified with the SCID-IV (First, Spitzer, Gibbon, &amp; Williams, 1995). Urinalysis was used to screen for drugs of abuse (cannabis, amphetamine, opioids, cocaine, benzodiazepines) on the day of testing and excluded if results were positive.</p> <p>A portion of this large sample took part in two separate fMRI sessions, which each included one-hour of behavioral testing and a one-hour scan on the same day. Participants were recruited from the parent study to participate in the fMRI portion if they successfully completed all previous testing sessions, and did not meet the following additional exclusion criteria: history of significant medical illness, contraindications for MRI (including pregnancy), any mood-altering medication on scan day (based on self-report), vision that was insufficient to see task stimuli, and left-handedness.</p> <p>After receiving a thorough explanation, all participants gave written informed consent according to the procedures approved by the University of California Los Angeles Institutional Review Board.</p> <!-- <p>Additional information can be found on the <a href="http://www.phenowiki.org/wiki/index.php/LA5C" target="_blank">study wiki</a>.</p> --> <p>Modalities Include:</p> <p>T1-weighted Anatomical MPRAGE</p> <p>64 Direction DWI</p> <p>BOLD contrast fMRI</p> <p>Resting State (with physiological monitoring)</p> <p>Breath Hold fMRI (with physiological monitoring)</p> <p>Balloon Analog Risk Task (BART) fMRI</p> <p>Stopsignal Task fMRI</p> <p>Taskswitching fMRI</p> <p>Spatial Working Memory Capacity Tasks (SCAP) fMRI</p> <p>Paired Associates Memory Task - Encoding/Retrieval (PAMenc/PAMret)</p> <p>Note:&nbsp;<em>Some of the T1-weighted images included within this dataset &nbsp;(around 20%) show an aliasing artifact potentially generated by a headset. The artifact renders as a ghost that may overlap the cortex through one or both temporal lobes. A list of participants showing the artifact has will be&nbsp;added to the dataset in upcoming revision 1.0.5.</em></p> 273 Siemens Trio (2 Imaging Sites) PDDL
Female action video game players.
  1. Lauren Sergio
  2. Diana Gorbet
ds000253 <p>Functional MRI was used to examine brain activity in experienced, female action video game players and in females who do not play action video games. Participants performed two visually-guided reaching conditions: 1) Standard condition in which the eyes and hand moved to the same cued spatial location, 2) Non-Standard/Dissociated condition in which the eyes moved to the cued spatial location but the hand moved 180 degrees in the opposite direction. A slow event-related protocol was used with each trial containing a cue period, an instructed-delay period, and a movement period. Four imaging runs were collected containing both conditions (in random order). An independent localizer run was also collected using a similar trial structure.</p> 20 Siemens TrioTim PDDL
High-resolution 7-Tesla fMRI data on the perception of musical genres
  1. Jörg Stadler
  2. Falko R. Kaule
  3. Michael Casey
  4. J. Swaroop Guntupalli
  5. Christian Häusler
  6. Richard Dinga
  7. Michael Hanke
ds000113b <p>This is an extension to the studyforrest dataset (http://studyforrest.org, see also ds113). This release adds more high-resolution, ultra high-field (7 Tesla) fMRI data from the same individuals. The twenty participants were repeatedly stimulated with a total of 25 music clips, with and without speech content, from five different genres using a slow event-related paradigm. The data release includes raw fMRI data, as well as pre-computed structural alignments for within-subject and group analysis. In addition to fMRI, simultaneously recorded cardiac and respiratory traces, as well the complete implementation of the stimulation paradigm, including stimuli, and extracted auditory features are provided.</p> 20 7 Tesla Siemens MAGNETOM PDDL
T1-weighted structural MRI study of cannabis users at baseline and 3 years follow up
  1. Lieuwe de Haan
  2. Anneke E. Goudriaan
  3. Dick J. Veltman
  4. Marise W. J. Machielsen
  5. Carin J. Meijer
  6. Reinout W. Wiers
  7. Wim van den Brink
  8. Wilhelmina A.M. Vingerhoets
  9. Janna Cousijn
  10. Laura Koenders
ds000174 <p>Heavy cannabis users (N=20, age baseline M=20.5, SD=2.1) and&nbsp;non-cannabis using healthy controls (N=22, age baseline M=21.6, SD=2.45) underwent a comprehensive psychological assessment and a T1-weighted structural MRI scan at baseline and 3 years follow-up.</p> <p>All structural MRI scans were acquired using a 3T MRI scanner (Intera, Philips Healthcare, Best, The Netherlands) with a phased array SENSE eight-channel receiver head coil. For each participant, a T1-weighted structural MRI image was acquired (T1 turbo field echo, TR 9.6 s, TE 4.6 s, 182 slices, slice thickness 1.2 mm, FOV 256x256 mm, in-plane resolution 256x256 mm, flip angle 8 degrees).</p> <p><strong>Data in this dataset</strong>: T1-weighted high-resolution structural</p> 42 Philips Intera 3T CC BY-NC
Visual imagery and false memory for pictures
  1. Gildas Brébion
  2. Ana María Sánchez Laforga
  3. Susana Ochoa
  4. Daniel Muñoz-Samons
  5. Carl Senior
  6. Sara Siddi
  7. Christian Stephan-Otto
ds000203 <p>Visual mental imagery might be critical in the ability to discriminate imagined from perceived pictures. Our aim was to investigate the neural bases of this specific type of reality-monitoring process in individuals with high visual imagery abilities. Methods: A reality-monitoring task was administered to twenty-six healthy participants using functional magnetic resonance imaging. During the encoding phase, 45 words designating common items, and 45 pictures of other common items, were presented in random order. During the retrieval phase, participants were required to remember whether a picture of the item had been presented, or only a word. Two subgroups of participants with a propensity for high vs. low visual imagery were contrasted.</p> 26 1.5T General Electric Signa HDe scanner PDDL
Adjudicating between face-coding models with individual-face fMRI responses
  1. Nikolaus Kriegeskorte
  2. Johan D Carlin
ds000232 <p>The perceptual representation of individual faces is often explained with reference to a norm-based face space. In such spaces, individuals are encoded as vectors where identity is primarily conveyed by direction and distinctiveness by eccentricity. Here we measured human fMRI responses and psychophysical similarity judgments of individual face exemplars, which were generated as realistic 3D animations using a computer-graphics model. We developed and evaluated multiple neurobiologically plausible computational models, each of which predicts a representational distance matrix and a regional-mean activation profile for 24 face stimuli. In the fusiform face area, a face-space coding model with sigmoidal ramp tuning provided a better account of the data than one based on exemplar tuning. However, an image-processing model with weighted banks of Gabor filters performed similarly. Accounting for the data required the inclusion of a measurement-level population averaging mechanism that approximates how fMRI voxels locally average distinct neuronal tunings. Our study demonstrates the importance of comparing multiple models and of modeling the measurement process in computational neuroimaging.</p> 10 3T MRI (Siemens Tim Trio) PDDL
Who can afford self-control? The neural efficiency mechanism explains effective self-regulation of behavior
  1. Marcel Falkiewicz
  2. Bartłomiej Kucharzyk
  3. Magdalena Senderecka
  4. Edward Nęcka
ds000148 <p>Dataset related to &quot;Who can afford self-control? The neural efficiency mechanism explains effective self-regulation of behavior&quot; (under revision). The task used was object 2-back, with targets at n-2 and lures at n-1 position. The subjects were required to press a response button when the target was present and refrain from reacting when a lure was presented. Each subject completed three runs. Psychometric assessment included Raven&#39;s Advanced Progressive Matrices and TAO and trait self-control questionnaire, AS36.</p> 49 GE Discovery MR 750 PDDL
Classification learning
  1. Gluck, M.A.
  2. Poldrack, R.A.
  3. Aron, A.R.
ds000002 <p>Subjects performed a classification learning task with two different problems (across different runs), using a &quot;weather prediction&quot; task. &nbsp;In one (probabilistic) problem, the labels were probabilistically related to each set of cards. &nbsp;In another (deterministic) problem, the labels were deterministically related to each set of cards. &nbsp;After learning, subjects participated in an event-related block of judgment only (no feedback) in which they were presented with stimuli from both of the training problems.</p> <p>&nbsp;</p> <p><strong>Note (30 Jan 2016): It was reported that the anatomical volumes for subjects sub016 and sub017 are identical. Updated data downloads will be available soon.</strong></p> <p><span style="color:#FF0000"><strong>Note (22 Feb 2016): In addition to the above note, it was found that some subjects highres001 and inplane data did not seem to be from the same person. We advise using this dataset with caution until these issues are corrected.</strong></span></p> <p>&nbsp;</p> 17 3 T Siemens Allegra MRI scanner PDDL
Flanker task (event-related)
  1. Milham MP
  2. Castellanos FX
  3. Biswal BB
  4. Uddin LQ
  5. Kelly AMC
ds000102 <p>The &quot;NYU Slow Flanker&quot; dataset comprises data collected from 26 healthy adults while they performed a slow event-related Eriksen Flanker task. **Please note that all data have been uploaded regardless of quality- it is up to the user to check for data quality (movement etc).</p> <p>On each trial (inter-trial interval (ITI) varied between 8 s and 14 s; mean ITI=12 s),participants used one of two buttons on a response pad to indicate the direction of a central arrow in an array of 5 arrows. In congruent trials the flanking arrows pointed in the same direction as the central arrow (e.g., &lt; &lt; &lt; &lt; &lt;), while in more demanding incongruent trials the flanking arrows pointed in the opposite direction (e.g., &lt; &lt; &gt; &lt; &lt;).</p> <p>Subjects performed two 5-minute blocks, each containing 12 congruent and 12 incongruent trials, presented in a pseudorandom order.</p> <p>Functional imaging data were acquired using a research dedicated Siemens Allegra 3.0 T scanner, with a standard Siemens head coil, located at theNYU Center for Brain Imaging. We obtained 146 contiguous echo planar imaging (EPI) whole-brain functional volumes (TR=2000 ms; TE=30 ms; flip angle=80, 40 slices, matrix=64x64; FOV=192 mm; acquisition voxel size=3x3x4mm) during each of the two flanker task blocks. A high-resolution T1-weighted anatomical image was also acquired using a magnetization prepared gradient echo sequence (MPRAGE, TR=2500 ms; TE= 3.93 ms; TI=900 ms; flip angle=8; 176 slices, FOV=256 mm).</p> <p>Please cite one of these papers listed below if you use these data.</p> 26 Siemens Allegra PDDL
Phonological memory in sign language relies on the visuomotor neural system outside the left hemisphere language network
  1. Yuji Kanazawa
ds000237 <p>Using functional magnetic resonance imaging, the present study investigated neural activation while bilinguals of spoken and signed language were engaged in a sequence memory span task. On each trial, participants viewed a nonsense syllable sequence presented either as written letters or as fingerspelling (4-7 syllables in length) and then held the syllable sequence for 12 s. Behavioral analysis revealed that participants relied on phonological memory while holding verbal information regardless of the type of input modality. At the neural level, this maintenance stage broadly activated the left-hemisphere language network, including the inferior frontal gyrus, supplementary motor area, superior temporal gyrus and inferior parietal lobule, for both letter and fingerspelling conditions.</p> 13 Siemens Trio 3 T head scanner with 32 channel phased-array head coil PDDL
MRI data of 3-12 year old children and adults during viewing of a short animated film
  1. Rebecca Saxe
  2. Alexa Riobueno-Naylor
  3. Grace Lisandrelli
  4. Hilary Richardson
ds000228 <p>Participants watched a silent version of Disney Pixar&#39;s &quot;Partly Cloudy,&quot; a 5.6-minute animated movie. The movie was preceded by 10s of rest, and participants were instructed to watch the movie and remain still.</p> 155 3-Tesla Siemens Tim Trio; Syngo MR B17A PDDL
Rhyme judgment
  1. Poldrack, R.A.
  2. Xue, G.
ds000003 <p>Subjects were presented with pairs of either words or pseudowords, and made rhyming judgments for each pair.</p> 13 TBA PDDL
Simultaneous fMRI/eyetracking while movie watching, plus visual localizers
  1. Jörg Stadler
  2. Daniel Kottke
  3. Vittorio Iacovella
  4. Michael Hoffmann
  5. Christian Häusler
  6. J. Swaroop Guntupalli
  7. Florian J. Baumgartner
  8. Ayan Sengupta
  9. Falko R. Kaule
  10. Michael Hanke
ds000113d <p>Extension of the studyforrest.org dataset published in Hanke et al. (2014; <a href="http://www.nature.com/articles/sdata20143" target="_blank">doi:10.1038/sdata.2014.3</a>) with additional acquisitions for 15 of the original 20 particpants. These additions include: retinotopic mapping, a localizer paradigm for higher visual areas (FFA, EBA, PPA), and another 2 hour&nbsp;movie recording with 3T full-brain BOLD fMRI with simultaneous 1000 Hz eyetracking.</p> <h4>Alternative Data Access</h4> <p>This dataset may also be accessed using git/git-annex. Please refer to the github project page:&nbsp;<a href="https://github.com/psychoinformatics-de/studyforrest-data-phase2" target="_blank">studyforrest-data-phase2</a>&nbsp;&nbsp;for more information.</p> 31 Philips Achieva 3T PDDL
Mixed-gambles task
  1. Poldrack R.A.
  2. Trepel C.
  3. Fox C.R.
  4. Tom S.M.
ds000005 <p>Subjects were presented with mixed (gain/loss) gambles, and decided whether they would accept each gamble. &nbsp;No outcomes of these gambles were presented during scanning, but after the scan three gambles were selected at random and played for real money.</p> 16 3T Siemens AG (Erlangen, Germany) Allegra MRI scanner PDDL
Stop-signal task with spoken & manual responses
  1. Poldrack RA
  2. Aron AR
  3. Xue G
ds000007 <p>Subjects performed a stop-signal task with one of three response types: manual response, spoken letter naming, and spoken pseudoword naming.</p> 20 3T Siemens Allegra MRI scanner PDDL
Balloon Analog Risk-taking Task
  1. Russell A. Poldrack
  2. Craig Fox
  3. Christopher Trepel
  4. Tom Schonberg
ds000001 <p>Subjects perform the Balloon Analog Risk-taking Task in an event-related design.</p> <p>Note: The original highres image for sub004 was not available, so the skull-stripped version is included as highres001.nii.gz</p> 16 Siemens Allegra 3T PDDL
Living-nonliving decision with plain or mirror-reversed text
  1. R Poldrack
  2. F Cazalis
  3. E Stover
  4. K Jimura
ds000006 <p>Subjects performed a living-nonliving decision on items presented in either plain or mirror-reversed text.&nbsp; ds000006A represents the first session and ds000006B represents the second session.</p> 14 Siemens Allegra 3T PDDL
Classification learning and stop-signal (1 year test-retest)
  1. Poldrack
  2. Aron
  3. Rizk-Jackson
ds000017 <p>A group of eight subjects performed two tasks (selective stop-signal and probabilistic classification) on two different occasions separated by about one year. &nbsp;ds000017A reflects data from timepoint 1 and&nbsp;ds000017B reflects data from timepoint 2.</p> 8 3T Siemens Allegra MRI scanner PDDL
The generality of self-control
  1. Russell Poldrack
  2. Jessica Cohen
ds000009 <p>This study examined four different forms of self-control in a single context to determine whether multiple forms were related in a single sample of healthy adults. Participants performed four different tasks within a single scanning session.</p> 24 Siemens Trio PDDL
A high-resolution 7-Tesla fMRI dataset from complex natural stimulation with an audio movie
  1. Jörg Stadler
  2. Wolf Zinke
  3. Oliver Speck
  4. Stefan Pollmann
  5. Falko R. Kaule
  6. Pierre Ibe
  7. Florian J. Baumgartner
  8. Michael Hanke
ds000113 <p>This is a high-resolution functional magnetic resonance (fMRI) dataset &mdash;&nbsp;20 participants recorded at high field strength (7 Tesla) during prolonged stimulation with an&nbsp;auditory feature film (&quot;Forrest Gump&#39;&#39;). In addition, a comprehensive set of&nbsp;auxiliary data (T1w, T2w, DTI, susceptibility-weighted image, angiography) as&nbsp;well as measurements to assess technical and physiological noise components&nbsp;have been acquired. An initial analysis confirms that these data can be used to&nbsp;study common and idiosyncratic brain response pattern to complex auditory&nbsp;stimulation. Among the potential uses of this dataset is the study of auditory&nbsp;attention and cognition, language and music perception as well as social&nbsp;perception. &nbsp;The auxiliary measurements enable a large variety of additional&nbsp;analysis strategies that relate functional response patterns to structural&nbsp;properties of the brain. Alongside the acquired data, we provide source code and&nbsp;detailed information on all employed procedures &mdash; from stimulus creation to&nbsp;data analysis. The total size of dataset is more than 350 GB. Therefore files for individual modalities are made available below. README.dataset_content provides an overview of the dataset and a description of the content for all available downloads. Note, access to individual files is possible via openfmri.org&#39;s XNAT server.</p> <p>&nbsp;</p> <p>Additional resources:</p> <p>More information and updates are made available at:&nbsp;<a href="http://www.studyforrest.org">http://www.studyforrest.org</a></p> <p>Source code repository:&nbsp;<a href="http://github.com/hanke/gumpdata">http://github.com/hanke/gumpdata</a></p> <p>Documentation for the source code:&nbsp;<a href="http://gumpdata.readthedocs.org">http://gumpdata.readthedocs.org</a></p> 20 7 Tesla Siemens MAGNETOM and 3 Tesla Philips Achieva PDDL
Prefrontal-Subcortical Pathways Mediating Successful Emotion Regulation
  1. Ochsner KN
  2. Lindquist MA
  3. Hughes BL
  4. Davidson ML
  5. Wager TD
ds000108 <p>Although prefrontal cortex has been implicated in the cognitive regulation of emotion, the cortical-subcortical interactions that mediate this ability remain poorly understood. To address this issue, we identified a right ventrolateral prefrontal region (vlPFC) whose activity correlated with reduced negative emotional experience during cognitive reappraisal of aversive images. We then applied a pathway-mapping analysis on subcortical regions to locate mediators of the association between vlPFC activity and reappraisal success (i.e., reductions in reported emotion). Results identified two separable pathways that together explained approximately 50% of the reported variance in self-reported emotion: (1) a path through nucleus accumbens that predicted greater reappraisal success, and (2) a path through ventral amygdala that predicted reduced reappraisal success (i.e., more negative emotion). These results provide direct evidence that vlPFC is involved in both the generation and regulation of emotion through different subcortical pathways, suggesting a general role for this region in appraisal processes.</p> 34 1.5T GE Signa Twin Speed Excite HD scanner (GE Medical Systems) PDDL
Integration of sweet taste and metabolism determines carbohydrate reward-study 3
  1. Dana M Small
  2. Martin Yeomans
  3. Elizabeth Garcia
  4. Nils B Kroemer
  5. Wambura Fobbs
  6. Barkha Patel
  7. Richard Keith Babbs
  8. Maria Geraldine Veldhuizen
ds000231 <p>Non-caloric beverages were mixed from novel flavors, citric acid, sucralose and food coloring. Participants, with 3 similarly liked but differently flavored and colored beverages who were unable to detect maltodextrin participated in 6 exposure sessions during which each beverage was consumed 6 times consistently paired with one of 3 caloric loads (0,112.5 and 150 kcal). An fMRI session followed in which participants sampled the non-caloric versions of the 3 exposed beverage (CS-, CS112.5, and CS150), as well as a tasteless and odorless control solution.</p> 9 Siemens TrioTim Syngo MR B17 PDDL
AK6
  1. James V. Haxby
  2. Hervé Abdi
  3. Yu-Chien Wu
  4. Yaroslav O. Halchenko
  5. Michael Hanke
  6. Jason Gors
  7. J. Swaroop Guntupalli
  8. Andrew C. Connolly
ds000241 <div>Subjects viewed images for six different classes of animals while being scanned with fMRI.</div> 12 Philips Achieva Intera 3T CC0
Physiological Contribution in Spontaneous Oscillations: An Approximate Quality - Assurance Index for Resting-State fMRI Signals
  1. Chen, JH
  2. Wu, CW
  3. Fan, HY
  4. Chao, YP
  5. Chou, KH
  6. Hsu, AL
ds000172 <p>For validating the sensitivity of the proposed PICSO index (a new quality-assurance index for resting state fMRI) to functional connectivity, both fMRI dataset of phantom and human during resting state were acquired. The resting-state human dataset (n=12, age: 26.4 &plusmn; 2.1 y, females/males: 6/6) was acquired at four image resolutions:</p> <p>1.3 &times; 1.3 &times; 2 mm3</p> <p>2 &times; 2 &times; 2 mm3</p> <p>3 &times; 3 &times; 3 mm3</p> <p>5 &times; 5 &times; 5 mm3</p> <p>Moreover, a spherical water phantom was scanned using identical imaging protocols. Besides, T1-weighted structural images and B0 field map were acquired as well.</p> <p>Code and same data are included as well.</p> 12 Siemens 3T Trio system with a 12-channel head coil. PDDL
A test-retest fMRI dataset for motor, language and spatial attention functions.
  1. Pernet CR
  2. Wardlaw JM
  3. Whittle IR
  4. Bastin ME
  5. Storkey A
  6. Gorgolewski KJ
ds000114 <p>A test-retest dataset was acquired to validate fMRI tasks used in pre-surgical planning. In particular, five task-related fMRI time series (finger, foot and lip movement, overt verb generation, covert verb generation, overt word repetition, and landmark tasks) were used to investigate which protocols gave reliable single-subject results. Ten healthy participants in their fifties were scanned twice using an identical protocol 2-3 days apart. In addition to the fMRI sessions, high-angular resolution diffusion tensor MRI (DTI), and high-resolution 3D T1-weighted volume scans were acquired.</p> 10 GE Signa HDxt 1.5T PDDL
Simon task
  1. Milham MP
  2. Kelly AMC
ds000101 <p>The &quot;NYU Simon Task&quot; dataset comprises data collected from 21 healthy adults while they performed a rapid event-related Simon task. **Please note that all data have been uploaded regardless of quality- it is up to the user to check for data quality (movement etc).</p> <p>On each trial (inter-trial interval (ITI) was 2.5 seconds, with null events for jitter), a red or green box appeared on the right or left side of the screen. Participants used their left index finger to respond to the presentation of a green box, and their right index finger to respond to the presentation of a red box.In congruent trials the green box appeared on the left or the red box on the right, while in more demanding incongruent trials the green box appeared on the right and the red on the left.</p> <p>Subjects performed two blocks, each containing 48 congruent and 48 incongruent trials, presented in a pre-determined order (as per OptSeq), interspersed with 24 null trials (fixation only).</p> <p>Functional imaging data were acquired using a research dedicated Siemens Allegra 3.0 T scanner, with a standard Siemens head coil, located at the NYU Center for Brain Imaging.</p> <p>We obtained 151 contiguous echo planar imaging (EPI) whole-brain functional volumes (TR=2000 ms; TE=30 ms; flip angle=80, 40 slices, matrix=64x64; FOV=192 mm; acquisition voxel size=3x3x4mm) during each of the two simon task blocks. A high-resolution T1-weighted anatomical image was also acquired using a magnetization prepared gradient echo sequence (MPRAGE, TR=2500 ms; TE= 3.93 ms; TI=900 ms; flip angle=8; 176 slices, FOV=256 mm).</p> <p>These data have not been published previously.</p> 21 Siemens Allegra 3.0 T scanner PDDL
EUPD Cyberball
  1. Jeremy Hall
  2. Douglas Steele
  3. Katie Nicol
  4. Merrick Pope
  5. Liana Romaniuk
ds000214 <p>Participants</p> <p>Twenty people with borderline personality disorder were recruited from outpatient and support services from around Edinburgh, Scotland. Diagnoses were confirmed using the Structured Clinical Interview for DSM-IV (SCID-II). Current symptoms were assessed using the Zanarini Rating Scale for Borderline Personality Disorder (ZAN-BPD). Adverse childhood events were assessed using the Childhood Trauma Questionnaire (CTQ). Fifteen BPD participants were receiving antidepressant medication and twelve were taking antipsychotic medication. Twenty age- and sex-matched controls were recruited from the community, however four were excluded due to technical issues during scanning, leaving sixteen controls. Exclusion criteria for all participants included pregnancy, MRI contraindications, diagnosis of a psychotic disorder, previous head injury or current illicit substance dependence. Controls met the additional criteria of no personal or familial history of major mental illness. Ethical approval was obtained from the Lothian National Health Service Research Ethics Committee, and all participants provided written informed consent before taking part.</p> <p>Experimental task</p> <p>Participants performed the Cyberball social exclusion task during functional magnetic resonance imaging (fMRI), adapted from a previous implementation by Kumar et al 2009. The task involves playing &ldquo;catch&rdquo; with two computer-controlled players, during which the participant can be systematically included or excluded from the game. We used this task as it assesses neural responses to social exclusion, is known to activate a range of social brain regions and is amenable to reinforcement learning modelling. The task was modified such that inclusion was varied parametrically over four levels: 0%, 33%, 66% and 100%, achieved by arranging the task into blocks of nine throws, respectively involving zero, one, two or three throws to the participant. Here, 100% inclusion means the degree to which the participant was included was equal to that of the other two players, with each receiving three throws per nine-throw block. Participants were asked to imagine that the other players were real, as exclusion by both human or simulated players has been previously reported to be similarly distressing. When the participant received the ball, they indicated which computer player they wished to throw the ball to with a button press. There were four repetitions of each inclusion level, providing 16 experimental blocks in total, with the first block being 100% inclusion, and all subsequent blocks being randomised. Each throwing event had a mean duration of 2700ms, with each being preceded by randomised jitter that was in part adjusted to accommodate the participant&rsquo;s reaction time from the previous trial, when applicable. This was achieved by comparing the total duration of the previous trial, including reaction time, with the ideal trial time of 2700ms: if this value was exceeded, a random jitter between 0 and 1000ms was subtracted from the mean jitter time of 1500ms; otherwise, the random jitter was added to 1500ms. Jitter therefore varied between 500ms and 2500ms. Mean block duration was 24s, with onsets denoted by the appearance of the cartoon figures following rest, and offsets by the conclusion of the final throw animation. Blocks were randomized, and interleaved with 13s rest blocks. Within blocks, throwing events were jittered to permit event disambiguation for reinforcement learning analysis.</p> 36 3T Siemens Magnetom Verio scanner PDDL
Resting State Perfusion in Healthy Aging
  1. Maria A. Fernandez-Seara
  2. José L. Zubieta
  3. Mario Riverol
  4. Miriam Recio
  5. Marta Vidorreta
  6. Reyes Garcia de Eulate
  7. Alvaro Galiano
ds000240 <p>The present study combined structural and functional neuroimaging techniques to evaluate aging related brain changes. Changes in brain structure were assessed by means of high resolution T1-weighted anatomical imaging and voxel-based morphometry. Functional changes were measured using ASL fMRI and analyzed by a model-free approach, independent component analysis.</p> 63 Siemenes 3T VB19 PDDL
Associative processing is inherent in scene perception
  1. Elissa M. Aminoff and Michael J. Tarr
ds000149 <p>How are complex visual entities such as scenes represented in the human brain? More concretely, along what visual and semantic dimensions are scenes encoded in memory? One hypothesis is that global spatial properties provide a basis for categorizing the neural response patterns arising from scenes. In contrast, non-spatial properties, such as single objects, also account for variance in neural responses. The list of critical scene dimensions has continued to grow &ndash; sometimes in a contradictory manner &ndash; coming to encompass properties such as geometric layout, big/small, crowded/sparse, and three-dimensionality. We demonstrate that these dimensions may be better understood within the more general framework of associative properties. That is, across both the perceptual and semantic domains, features of scene representations are related to one another through learned associations. Critically, the components of such associations are consistent with the dimensions that are typically invoked to account for scene understanding and its neural bases. Using fMRI, we show that non-scene stimuli displaying novel associations across identities or locations recruit putatively scene-selective regions of the human brain (the parahippocampal/lingual region, the retrosplenial complex, and the transverse occipital sulcus/occipital place area). Moreover, we find that the voxel-wise neural patterns arising from these associations are significantly correlated with the neural patterns arising from everyday scenes providing critical evidence whether the same encoding principals underlie both types of processing. These neuroimaging results provide evidence for the hypothesis that the neural representation of scenes is better understood within the broader theoretical framework of associative processing. In addition, the results demonstrate a division of labor that arises across scene-selective regions when processing associations and scenes providing better understanding of the functional roles of each region within the cortical network that mediates scene processing.</p> 15 3T Siemens Verio MR scanner PDDL
MEG-BIDS Brainstorm data sample
  1. Sylvain Baillet
  2. François Tadel
  3. Jeremy Moreau
  4. Elizabeth Bock
  5. Guiomar Niso
ds000246 <p>This dataset is a MEG-BIDS version of a tutorial dataset of Brainstorm, a free and open application for MEG data analysis (Tadel et al. 2011). This sample has been organized according to the specifications of MEG-BIDS to obtain feedback from the user community.</p> <p>Tadel F, Baillet S, Mosher JC, Pantazis D, Leahy RM, &ldquo;Brainstorm: A User-Friendly Application for MEG/EEG Analysis,&rdquo; Computational Intelligence and Neuroscience, vol. 2011, Article ID 879716, 13 pages, 2011. doi:10.1155/2011/879716</p> 1 MEG, CTF Inc. 275 channels CC0
Auditory and Visual Oddball EEG-fMRI
  1. Paul Sajda
  2. Truman R Brown
  3. Bryan Conroy
  4. Jordan Muraskin
  5. Robin I Goldman
  6. Jennifer M Walz
ds000116 <p>Healthy subjects performed separate but analogous auditory and visual oddball tasks (interleaved), while we recorded simultaneous EEG-fMRI.</p> 17 3T Philips Achieva PDDL
The heterogeneity in retrieved relations between the personality trait 'Harm avoidance' and gray matter volumes due to variations in the VBM and ROI labeling processing settings
  1. Johan De Mey
  2. Chris Baeken
  3. Peter Van Schuerbeek
ds000202 <p>In this study we tested the heterogeneity in obtained correlations between gray matter morphology and the personality trait &#39;Harm Avoidance&#39; (HA).</p> <p>95 healthy female volunteers (age: 18-30 years) were recruited to participate in the study. All underwent a T1 weighted anatomical scan of the head (TI/TR/TE=940.4/7.6/3.7ms, flip angle=8 degrees, FOV=240x240x200mm&sup3;, resolution=1x1x2mm&sup3;) at a Philips 3T Achieva MRI scanner. A score for all personality traits as defined in Cloninger&rsquo;s psychobiological model of personality was obtained using the &#39;Revised Temperament and Character Inventory&#39;&nbsp;(TCI).</p> 95 Philips 3T Achieva PDDL
Preschool Anxiety Disorders
  1. Kevin Pelphrey
  2. Pooja Gaur
  3. Allen W. Song
  4. Nan-Kuei Chen
  5. Helen L. Egger
  6. William E. Copeland
  7. Adrian Angold
  8. Kimberly L. H. Carpenter
ds000144 <div> <div> <h3>Objective</h3> <p>In this prospective, longitudinal study of young children, we examined whether a history of preschool generalized anxiety, separation anxiety, and/or social phobia is associated with amygdala-prefrontal dysregulation at school-age. As an exploratory analysis, we investigated whether distinct anxiety disorders differ in the patterns of this amygdala-prefrontal dysregulation.</p> </div> <div> <h3>Methods</h3> <p>Participants were children taking part in a 5-year study of early childhood brain development and anxiety disorders. Preschool symptoms of generalized anxiety, separation anxiety, and social phobia were assessed with the Preschool Age Psychiatric Assessment (PAPA) in the first wave of the study when the children were between 2 and 5 years old. The PAPA was repeated at age 6. We conducted functional MRIs when the children were 5.5 to 9.5 year old to assess neural responses to viewing of angry and fearful faces.</p> </div> <div> <h3>Results</h3> <p>A history of preschool social phobia predicted less school-age functional connectivity between the amygdala and the ventral prefrontal cortices to angry faces. Preschool generalized anxiety predicted less functional connectivity between the amygdala and dorsal prefrontal cortices in response to fearful faces. Finally, a history of preschool separation anxiety predicted less school-age functional connectivity between the amygdala and the ventral prefrontal cortices to angry faces and greater school-age functional connectivity between the amygdala and dorsal prefrontal cortices to angry faces.</p> </div> <div> <h3>Conclusions</h3> <p>Our results suggest that there are enduring neurobiological effects associated with a history of preschool anxiety, which occur over-and-above the effect of subsequent emotional symptoms. Our results also provide preliminary evidence for the neurobiological differentiation of specific preschool anxiety disorders.</p> </div> </div> 45 3T GE Signa EXCITE HD; 3T GE MR750 CC0
Distinct brain systems mediate the effects of nociceptive input and self-regulation on pain
  1. Tor D. Wager
  2. Jason T. Buhle
  3. Mathieu Roy
  4. Choong-Wan Woo
ds000140 <p>Cognitive self-regulation can strongly modulate pain and emotion. However, it is unclear whether self-regulation primarily influences primary nociceptive and affective processes or evaluative ones. In this study, participants engaged in self-regulation to increase or decrease pain while experiencing multiple levels of painful heat during fMRI imaging. Both heat intensity and self-regulation strongly influenced reported pain, but they did so via two distinct brain pathways. The effects of stimulus intensity were mediated by the Neurologic Pain Signature (NPS), an a priori distributed brain network shown to predict physical pain with over 90% sensitivity and specificity across four studies. Self-regulation did not influence NPS responses; instead, its effects were mediated through functional connections between the nucleus accumbens and ventromedial prefrontal cortex. This pathway was unresponsive to noxious input, and has been broadly implicated in valuation, emotional appraisal, and functional outcomes in pain and other types of affect. These findings provide evidence that pain reports are associated with two dissociable functional systems: nociceptive/affective aspects mediated by the NPS, and evaluative/functional aspects mediated by a fronto-striatal system.</p> 33 3T Philips Achieva TX scanner PDDL
Offline Processing in Associative Learning
  1. J. David Creswell
  2. Michael J. Tarr
  3. Adrian Nestor
  4. James K. Bursley
ds000168 <p>This is structural and functional MRI data from 35 healthy volunteers that accompanies Bursley et al. (2015), &quot;Awake, Offline Processing During Associative Learning.&quot; Subjects encoded paired associates and then performed a distractor task before being probed on associate pairs. Pattern analyses suggest that encoded memories were reactivated during the distractor task, and performance of the distractor task led to superior recall for the associate pairs, compared to a control condition in which no distractor task was performed.</p> <p><strong>In this dataset</strong>: High-resolution T1-weighted structural and BOLD contrast fMRI scans</p> 35 Siemens 3T MAGNETOM Verio PDDL
Modafinil alters intrinsic functional connectivity of the right posterior insula: a pharmacological resting state fMRI study
  1. Stefano L. Sensi
  2. Armando Tartaro
  3. Nicoletta Cera
ds000133 <p>Modafinil is employed for the treatment of narcolepsy and has also been, off-label, used to treat cognitive dysfunction in neuropsychiatric disorders. &nbsp;In a previous study, we have reported that single dose administration of modafinil in healthy young subjects enhances fluid reasoning and affects resting state activity in the Fronto Parietal Control (FPC) and Dorsal Attention (DAN) networks. No changes were found in the Salience Network (SN), a surprising result as the network is involved in the modulation of emotional and fluid reasoning. &nbsp;The insula is crucial hub of the SN and functionally divided in anterior and posterior subregions. Using a seed-based approach, we have now analyzed effects of modafinil on the functional connectivity (FC) of insular subregions. Analysis of FC with resting state fMRI (rs-FMRI) revealed increased FC between the right posterior insula and the putamen, the superior frontal gyrus and the anterior cingulate cortex in the modafinil-treated group.Modafinil is considered a putative cognitive enhancer. The rs-fMRI modifications that we have found are consistent with the drug cognitive enhancing properties and indicate subregional targets of action.</p> <p><strong>Dataset includes:</strong> BOLD contrast fMRI and high-resolution T1-weighted structural scans.</p> 26 Philips Achieva 3T PDDL
Learning and memory: motor skill consolidation and intermanual transfer
  1. Avi Karni
  2. David Manor
  3. Ella Gabitov
ds000170 <p>Participants were scanned during the performance of a finger-to-thumb opposition sequence (5-element), intensively trained a day earlier, and a similarly constructed, but novel, untrained sequence, using either their trained (left) or untrained hand. The imaging session consisted of 3 consecutive runs for each sequence and hand: Th &ndash; trained (left) hand, Uh &ndash; untrained (right) hand, T &ndash; trained sequence, U &ndash; untrained sequence. Experimental runs (each 144 seconds long) were separated by a 1.5 &ndash; 2 minutes break that included a verbal interaction with the participant. Each run consisted of two performance blocks (8 repetitions of a sequence paced by an auditory signal at a fixed rate of 1.66 Hz, during 24 sec each) separated by a rest interval of 30 seconds. Each run began and ended with a rest period of 36 seconds and 24 seconds, respectively.</p> <p>Functional magnetic resonance imaging (fMRI) scanning was carried out at the C. Sheba Medical Center, Tel-Hashomer, using a 3 Tesla whole body high definition system (GE EXCITE 3 HD) equipped with an 8-channel head coil. A high-resolution full-brain 3D structural images were acquired in the axial orientation using a T1*-weighted echo-planar sequence (TR = 7.3 ms, TE = 3 ms, flip angle = 20&deg;, FOV = 256 x 256 mm2, matrix size = 256 x 256 voxels, voxel size = 1 x 1 x 1 mm3). BOLD-sensitive functional images were obtained using a gradient echo-planar T2*-sequence (TR = 3000 ms, TE = 35 ms, flip angle=90&deg;, FOV = 220 x 220 mm2, matrix size = 64 x 64 voxels, voxel size = 3.4 x 3.4 x 3.4 mm3, no gap, ascending) with&nbsp;40 axial oblique slices, covering the whole brain.</p> <p><strong>Dataset contains:</strong> BOLD contrast fMRI and high resolution T1-weighted structural images.</p> 15 A 3 Tesla whole body high definition system (GE EXCITE 3 HD) equipped with an 8-channel head coil. PDDL
Stroop task
  1. Timothy D. Verstynen
ds000164 <p>Participants performed the color-word version of the Stroop task with three conditions (congruent, incongruent, and neutral) while in the MR scanner. Participants were instructed to ignore the meaning of the printed word and respond to the ink color in which the word was printed. Each condition was meant to elicit a certain level of attentional demand. Participants responded to ink color by pressing button under the index, middle, and ringe fingers on their right hand. One button for each color (red, green, and blue) on an MR-safe response box. Task begins with a 1,000ms fixation cross followed by the stroop stimulus for 2,000ms. The interstimulus interval between successive trial starts was sampled from an exponential distribution, between 3 and 20 s with a mean of 4 s and a median of 3 s, in order to ensure accurate deconvolution of the hemodynamic response. Conditions were pseudorandomized in an event related fashion. 120 trials were presented to each participant. Stimuli were back projected on a screen located at the back of the MR bore with an MR safe projector. Participants used a mirror attached at the top of the head coil to view. This study using response time as a behavioral variable.</p> 28 Siemen's Verio 3T with 32 channel head coil PDDL
Visual image reconstruction
  1. Yukiyasu Kamitani
  2. Norihiro Sadato
  3. Hiroki C. Tanabe
  4. Yusuke Morito
  5. Masa-aki Sato
  6. Okito Yamashita
  7. Hajime Uchida
  8. Yoichi Miyawaki
ds000255 <p>In this study, we reconstructed visual images by combining local image bases of multiple scales, whose contrasts were independently decoded from fMRI activity by automatically selecting relevant vox- els and exploiting their correlated patterns. Binary- contrast, 10 &times; 10-patch images (2^100 possible states) were accurately reconstructed without any image prior on a single trial or volume basis by measuring brain activity only for several hundred random images. Reconstruction was also used to identify the presented image among millions of candidates.</p> 2 Siemens MAGNETOM Trio A Tim 3T PDDL
Training of loss aversion modulates neural sensitivity toward potential gains
  1. Russell A. Poldrack
  2. W. Todd Maddox
  3. Ungi Kim
  4. Sagar Parikh
  5. Albert Elumn
  6. Nathan Giles
  7. Corey N. White
  8. Mei-Yen Chen
ds000053 <h3>Aims:</h3> <p>We investigated behavioral and neural mechanisms for modulating loss aversion.</p> <h3>Methods</h3> <p><strong>Behavior task</strong>: We adapted the gambling task (Tom et al., 2007) by introducing contexts and feedback that encourage participants to take more or less loss averse choices.</p> <p><strong>fMRI</strong>: We used general linear model to find brain activation that correlates with magnitude of potential gains or potential losses during the learning and post-learning probe. We also used psychophysiological interaction analysis (independent seeded at vmPFC) to identified the brain areas showing interaction with vmPFC over the course of training.</p> <h3>General findings and importance:</h3> <p>Training primarily modulated behavioral and neural sensitivity toward potential gains, and was reflected in connectivity between regions involved in cognitive control and those involved in value representation. These findings highlight the importance of experience in development of biases in decision-making.</p> <h3>Sample Size</h3> <p>Sixty human participants completed the behavioral paradigm in the MRI scanner (31 females, 29 males; age range: 18 -&nbsp;30 with mean 22.9-year-old). Two participants were discarded from the brain imaging analyses; one due to a missing anatomical image, and the other due to excessive head movement (more than one-third of the volumes were considered &ldquo;bad time points&rdquo; according to the motion correction procedures detailed in the Preprocessing section).</p> 60 Siemens Skyra 3T PDDL
Multi-resolution 7T fMRI data on the representation of visual orientation
  1. Michael Hanke
  2. Stefan Pollmann
  3. Oliver Speck
  4. Renat Yakupov
  5. Ayan Sengupta
ds000113c <h3>Dataset Description</h3> <p>This dataset consists of empirical ultra high-field fMRI data recorded at four<br /> spatial resolutions (0.8 mm, 1.4 mm, 2 mm, and 3 mm isotropic voxel size) for<br /> orientation decoding in visual cortex &mdash; in order to test hypotheses on the<br /> strength and spatial scale of orientation discriminating signals. This is an<br /> extension of the studyforrest project. All seven&nbsp;participants previously<br /> volunteered for the audio-only and the audio-visual Forrest Gump study. The<br /> dataset is compliant with the BIDS data description standard<br /> (<a href="http://bids.neuroimaging.io">http://bids.neuroimaging.io</a>). &nbsp;A detailed description can be found in:</p> <p><cite>Sengupta, A., Yakupov, R., Speck, O., Pollmann, S., Hanke, M. <strong>Ultra<br /> High-Field (7 Tesla) multi-resolution fMRI data on the representation<br /> of visual orientation</strong>. Data in Brief (submitted)</cite></p> <p>For more information about the project visit: <a href="http://studyforrest.org" target="_blank">http://studyforrest.org</a></p> <h4>Alternative Data Access</h4> <p>This dataset may also be accessed using git/git-annex. Please refer to the github project page:&nbsp;<a href="https://github.com/psychoinformatics-de/studyforrest-data-multires7t" target="_blank">studyforrest-data-multires7t</a>&nbsp;for more information.</p> 7 Siemens 7T PDDL
Spinal fMRI reveals decreased descending inhibition during secondary mechanical hyperalgesia
  1. Gierthmühlen J
  2. Jansen O
  3. Stroman PW
  4. Baron R
  5. Riedel C
  6. Wolff S
  7. Rempe T
ds000138 <div> <div> <div> <div> <p>Mechanical hyperalgesia is one distressing symptom of neuropathic pain which is explained by central sensitization of the nociceptive system. This sensitization can be induced experimentally with the heat/capsaicin sensitization model. The aim was to investigate and compare spinal and supraspinal activation patterns of identical mechanical stimulation before and after sensitization using functional spinal magnetic resonance imaging (spinal fMRI).</p> <p>Sixteen healthy subjects (6 female, 10 male, mean age 27.2 &plusmn; 4.0 years) were investigated with mechanical stimulation of the C6 dermatome of the right forearm during spinal fMRI. Testing was always performed in the area outside of capsaicin application (i.e. area of secondary mechanical hyperalgesia).</p> <p>During slightly noxious mechanical stimulation before sensitization, activity was observed in ipsilateral dorsolateral pontine tegmentum (DLPT) which correlated with activity in ipsilateral spinal cord dorsal gray matter (dGM) suggesting activation of descending nociceptive inhibition. During secondary mechanical hyperalgesia, decreased activity was observed in bilateral DLPT, ipsilateral/midline rostral ventromedial medulla (RVM), and contralateral subnucleus reticularis dorsalis, which correlated with activity in ipsilateral dGM. Comparison of voxel-based activation patterns during mechanical stimulation before/after sensitization showed deactivations in RVM and activations in superficial ipsilateral dGM.</p> <p>This study revealed increased spinal activity and decreased activity in supraspinal centers involved in pain modulation (SRD, RVM, DLPT) during secondary mechanical hyperalgesia suggesting facilitation of nociception via decreased endogenous inhibition. Results should help prioritize approaches for further in vivo studies on pain processing and modulation in humans.</p> </div> </div> </div> </div> 16 Philips Achieva 3T PDDL
Neural mechanism underlying appearance social comparison
  1. Xiao Gao
ds000213 <p>We investigated the neural basis of body image processing in overweight and average weight young women to understand whether brain regions that were previously found to be involved in processing self-reflective, perspective and affective components of body image would show different activation between two groups.</p> 26 3T Siemens TRIO MRI scanner PDDL
Route Learning
  1. Brice A Kuhl
  2. Serra E Favila
  3. Ashima Oza
  4. Avi JH Chanales
ds000217 <p>Subjects were scanned while learning 2 pairs of overlapping routes on the NYU campus. Subjects completed 14 rounds of route learning during which they viewed repetitions of the routes and learned to predict the destination of each. To encourage learning catch trials were included during which the route would stop in the middle and subjects would be asked to either identify 1) the final destination of that route or 2) the direction of the next turn in the route (right/left). After exiting the scanner subjects completed a picture test in which they were shown still images selected from the routes and were asked to identify the destination associated with each image. Two independent experiments were performed using different sets of routes.</p> <p>&nbsp;</p> <p>Link to a sample task video (also present in dataset): https://www.youtube.com/watch?v=vqp2m2Lx49k</p> 41 Siemens Allegra 3T PDDL
Task-related concurrent but opposite modulations of overlapping functional networks as revealed by spatial ICA
  1. MN Potenza
  2. J Monterosso
  3. VD Calhoun
  4. S Zhang
  5. J Xu
ds000122 <p>Animal studies indicate that different functional networks (FNs), each with a unique timecourse, may overlap at common brain regions. For understanding how different FNs overlap in the human brain and how the timecourses of overlapping FNs are modulated by cognitive tasks, we applied spatial independent component analysis (sICA) to functional magnetic resonance imaging (fMRI) data. These data were acquired from healthy participants while they performed a visual task with parametric loads of attention and working memory.&nbsp;</p> <p>Functional images were acquired using gradient-echo EPI scanning sequence (TR/ TE=1500/30ms, Flip angle=70 degrees, 26 slices, 3mm thick with 1.2 mm skip, 3.125 &times; 3.125 mm2 in plane pixels) with a Siemens Allegra 3T system. The scanning plane was off the AC-PC line rostrally at 20 degrees. The thin scanning slice and tilted scanning plane were used to reduce susceptibility-related signal loss at the basal forebrain (Deichmann et al 2003). Each participant had three functional runs, and each run used a different task script and acquired 258 volumes. The order of scripts was counterbalanced across participants.&nbsp;</p> 17 Siemens Allegra 3T PDDL
Individual Brain Charting
  1. Ana Luisa Grilo-Pinho
  2. Lucie Hertz-Pannier
  3. Bertrand Thirion
ds000244 <p>Functional Magnetic Resonance Imaging (fMRI) has opened the possibility to map all types of perceptual, motor or cognitive functions, providing an instrumental basis for the whole field of cognitive neuroimaging. However, no systematic data collection has so far been undertaken toward a fine spatial and systematic representation of mental functions. In order to attain to such a comprehensive atlas of brain responses, the Individual Brain Charting (IBC) project aims to provide a dataset that contains high-resolution multi-task fMRI data. These refer to a cohort of twelve participants performing many different tasks, yielding a precise mapping of the underlying functions, free from both inter-subject and inter-site variability. Additionally, the dataset is complemented with high-resolution anatomical and diffusion images, pertaining to a fine anatomical characterization of these brains.</p> 12 Siemens Prisma 3T CC0
Developmental changes in brain function underlying the influence of reward processing on inhibitory control (Slot Reward)
  1. Beatriz Luna
  2. Theresa Teslovich
  3. Sarah J. Ordaz
  4. Charles F. Geier
  5. Padmanabhan, Aarthi
ds000120 <p>Adolescence is a period marked by changes in motivational and cognitive brain systems. However, the development of the interactions between reward and cognitive control processing are just beginning to be understood. Using event-related functional neuroimaging and an incentive modulated antisaccade task, we compared blood-oxygen level dependent activity underlying motivated response inhibition in children, adolescents, and adults.</p> <p>AFNI (Analysis and Visualization of Functional Neuroimages) software (Cox, 1996) was used for individual subject deconvolution as well as subsequent group analyses. Deconvolution methods followed steps delineated previously (Ward, 1998). Briefly, our model consisted of two orthogonal regressors of interest for reward and neutral correct AS trials, as well as regressors for incorrect AS trials and all VGS trials. Linear and non-linear trends and six motion parameters were also included as nuisance regressors. A unique estimated impulse response function (i.e., hemodynamic response function) for each regressor of interest (correct reward and neutral AS trials) was determined by a weighted linear sum of eight sine basis functions multiplied by data determined least squares estimated beta weights. The estimated impulse response function reflects the estimated BOLD response to a type of trial (reward AS trial) after controlling for variations in the BOLD signal due to other regressors. We made no assumptions about the shape of the function. We specified the duration of the estimated response from the trial onset (0 seconds) to 24 seconds (17 TRs) post trial onset, a sufficient time window for the hemodynamic response to peak and return to baseline, which was defined as the jittered fixation periods between trials.</p> <p>&nbsp;</p> <p>&nbsp;</p> 27 3T Siemens Allegra MRI scanner PDDL
Moral judgments of intentional and accidental moral violations across Harm and Purity domains
  1. Amelia Brown
  2. James Dungan
  3. Jorie Koster-Hale
  4. Emily Wasserman
  5. Alek Chakroff
  6. Rebecca Saxe
  7. Liane Young
ds000212 <p>The purpose of this data is to investigate neural differences within regions associated with Theory of Mind across a) intentional vs accidental moral acts; b) across moral domains (harmful vs impure acts); c) across moral subdomains; d) between morally relevant and nonmoral scenarios. Subjects were scanned while completing a Theory of Mind localizer task, and while completing the moral judgment task. For each scenario, subjects saw a text-based version of the scenario, and rated its moral wrongness on a 1-4 scale. Each scenario text was presented in 4 serial segments, comprising Background, Action, Outcome, and Intent.</p> <p>&nbsp;</p> <p>For representational similarity analysis scripts: <a href="https://github.com/lypsychlab/RSA">https://github.com/lypsychlab/RSA</a></p> 39 Siemens 3T Trio PDDL
Visual object recognition
  1. Pietrini, P.
  2. Schouten, J.
  3. Ishai, A.
  4. Furey, M.
  5. Gobbini, M.
  6. Haxby, J.
ds000105 <p>Neural responses, as reflected in hemodynamic changes, were measured in six subjects (five female and one male) with gradient echo echoplanar imaging on a GE 3T scanner (General Electric, Milwaukee, WI) [repetition time (TR) = 2500 ms, 40 3.5-mm-thick sagittal images, field of view (FOV) = 24 cm, echo time (TE) = 30 ms, flip angle = 90] while they performed a one-back repetition detection task. High-resolution T1-weighted spoiled gradient recall (SPGR) images were obtained for each subject to provide detailed anatomy (124 1.2-mm-thick sagittal images, FOV = 24 cm). Stimuli were gray-scale images of faces, houses, cats, bottles, scissors, shoes, chairs, and nonsense patterns. The categories were chosen so that all stimuli from a given category would have the same base level name. The specific categories were selected to allow comparison with our previous studies (faces, houses, chairs, animals, and tools) or ongoing studies (shoes and bottles). Control nonsense patterns were phase-scrambled images of the intact objects. Twelve time series were obtained in each subject. Each time series began and ended with 12 s of rest and contained eight stimulus blocks of 24-s duration, one for each category, separated by 12-s intervals of rest. Stimuli were presented for 500 ms with an interstimulus interval of 1500 ms. Repetitions of meaningful stimuli were pictures of the same face or object photographed from different angles. Stimuli for each meaningful category were four images each of 12 different exemplars.</p> <p>&nbsp;</p> <p>Note that the original version of the raw data that was posted prior to 10/29/2012 had one extra timepoint incorrectly added to the end of runs 1-11 for each subject. &nbsp;The currently posted version has been corrected.</p> 6 GE 3T PDDL
Integration of sweet taste and metabolism determines carbohydrate reward - study 1
  1. Dana M Small
  2. Martin Yeomans
  3. Elizabeth Garcia
  4. Nils B Kroemer
  5. Wambura Fobbs
  6. Barkha Patel
  7. Richard Keith Babbs
  8. Maria Geraldine Veldhuizen
ds000229 <p>Non-caloric beverages were mixed from novel flavors, citric acid, sucralose and food coloring. For each session participants arrived to the lab fasted (4 hours). In the pre-conditioning session, participants were trained on how to use the scales to rate overall intensity, sweetness, liking, and wanting. Then participants rated each of the non-caloric stimuli 3 times. Average ratings were calculated and participants who rated 5 beverages as equally liked were asked to perform a triangle test to determine if they were able to reliably detect the presence of maltodextrin (DE = 12.5) in a beverage. Participants, with 5 similarly liked beverages who were unable to detect maltodextrin were then trained on the fMRI procedures. Meanwhile a second experimenter prepared the subject-specific beverage assignments so that color, flavors and caloric load were counterbalanced across subjects. The participant was then scheduled for 5 exposure sessions during which each beverage was consumed 6 times. Following the exposure sessions, subjects returned for a post-conditioning session where they rated the 10 non-caloric beverages for sweetness, liking, familiarity and wanting (as in the pre-conditioning session). An fMRI session followed in which participants sampled the non-caloric versions of the 5 exposed beverage (CS-, CS37.5, CS75, CS112.5, and CS150), as well as a tasteless and odorless control solution.</p> 15 Siemens Trio Tim Syngo MR B17 PDDL
Sequential Inference VBM
  1. Ray Dolan
  2. Shu-Chen Li
  3. Karl Friston
  4. Dorothea Hammerer
  5. Thomas FitzGerald
ds000222 <p>These data comprise behaviour from 79 subjects on a probabilistic reversal task together with T1-weighted structural images. (The task is described in more detail in: FitzGerald et al. Sequential inference as a mode of cognition and its correlates in fronto-parietal and hippocampal brain regions. PLoS Computational Biology (2017))<br /> <br /> The principal findings of the original study were that the majority of subjects employed a strategy of inferring about the joint probability of sequences of states stretching into the past, and that betwene-subject differences in strategy correlated with gery-matter density changes in various parts of the brain.<br /> <br /> Data were collected from 43 younger adults and 36 older adults. Additionally, most of the subjects performed the Raven&#39;s matrices task, and an n-back working memory task, and results from these are also included, together with height, weight, age and sex.</p> 79 Siemens Trio Magnetom 3T PDDL
Stop-signal task with unconditional and conditional stopping
  1. Poldrack, R.A.
  2. Smith, S.
  3. Frank, M.
  4. Behrens, T.E.
  5. Aron, A.R.
ds000008 <p>Subjects performed two versions of a stop signal task. &nbsp;In the unconditional stop-signal task, subjects are told to withhold their response whenever they hear a tone. &nbsp;In the conditional stop signal task, they are told to withhold their response if they hear the tone and the response is the one labeled as critical, whereas they should go ahead and respond if the response is the noncritical one.</p> <p>Revision history:</p> <p>12/20/2012: The originally posted version of this dataset was missing some onsets for task002. The newly posted version contains the full set of onsets for all conditions. &nbsp;If only the onsets and model info are needed, they can be obtained by downloading the updated onsets file and untarring it in the main ds008 directory.</p> <p>3/7/2016: Remove sub008 due to inconsistently defined onsets.</p> <p>5/22/2016: Converted to BIDS file structure</p> 15 3T Siemens Allegra MRI scanner PDDL
Whole-brain background-suppressed pCASL MRI with 1D-accelerated 3D RARE Stack-Of-Spirals Readout- Dataset 1
  1. John A. Detre
  2. María A. Fernández-Seara
  3. Yulin V. Chang
  4. Ze Wang
  5. Marta Vidorreta
ds000234 <p>We investigated the use of accelerated 3D readouts to obtain whole-brain, high-SNR ASL perfusion maps and reduce SAR deposition. Parallel imaging was implemented along the partition-encoding direction in a pseudo-continuous ASL sequence with background-suppression and 3D RARE Stack-Of-Spirals readout, and its performance was evaluated in three small cohorts. First, both non-accelerated and two-fold accelerated single-shot versions of the sequence were evaluated in healthy volunteers during a motor-photic task, and the performance was compared in terms of temporal SNR, GM-WM contrast, and statistical significance of the detected activation. Secondly, single-shot 1D-accelerated imaging was compared to a two-shot accelerated version to assess benefits of SNR and spatial resolution for applications in which temporal resolution is not paramount. Third, the efficacy of this approach in clinical populations was assessed by applying the single-shot 1D-accelerated version to a larger cohort of elderly volunteers.</p> 5 3T Siemens Tim Trio B17 PDDL
Neural Processing of Emotional Musical and Nonmusical Stimuli in Depression
  1. Cary R. Savage
  2. W. Kyle Simmons
  3. Rick E. Ingram
  4. Alicia A. Clair
  5. Laura E. Martin
  6. Evangelia Chrysikou
  7. Ruth Ann Atchley
  8. Rebecca J. Lepping
ds000171 <p>The present dataset uses functional MRI and an validated emotional music and nonmusical auditory paradigm (Lepping, et al., 2015) to examine how neural processing of emotionally provocative auditory stimuli is altered in depression. &nbsp;Nineteen individuals with depression (MDD) and 20 never-depressed control participants (ND) listened to positive and negative emotional musical and nonmusical stimuli during fMRI scanning. ND participants had no history of depression or other psychiatric disorder, determined by administration of the Structured Clinical Interview for DSM Disorders, non-patient version (SCID-I/NP) (First, 2002). &nbsp;Participants in the MDD group were all experiencing a current depressive episode at the time of scanning, determined by screening for research purposes using the SCID-I/NP. &nbsp;Participants had no current or past manic episodes, no comorbid anxiety disorders, and no current alcohol abuse or dependence, and were not taking medication for depression at the time of the study.</p> 39 Siemens Skyra 3T PDDL
Multiband Multi-Echo Imaging of Simultaneous Oxygenation and Flow Timeseries for Resting State Connectivity
  1. Yang Wang
  2. R. Marc Lebel
  3. Andrew S. Nencka
  4. Alexander D. Cohen
ds000216 <p>Multiband imaging was combined with with a multi-echo acquisition to collect whole-brain simultaneous pseudo-continuous arterial spin labeling (pCASL) and blood-oxygenation-level dependent (BOLD) echo-planar imaging (MBME ASL/BOLD). Resting-state connectivity in seven healthy adult subjects was assessed using this sequence. Four echoes were acquired with a multiband acceleration of four, in order to increase spatial resolution, shorten repetition time, and reduce slice-timing effects on the ASL signal. In addition, by acquiring four echoes, advanced multi-echo independent component analysis (ME-ICA) denoising could be employed to increase the signal-to-noise ratio (SNR) and BOLD sensitivity. Seed-based and dual-regression approaches were utilized to analyze functional connectivity. These metrics were compared between single echo (E2), multi-echo combined (MEC), multi-echo combined and denoised (MECDN), and perfusion-weighted (PW) timeseries.</p> 7 GE MR750, DV25 PDDL
Neural responses to naturalistic clips of behaving animals in two different task contexts
  1. James V. Haxby
  2. Andrew C. Connolly
  3. Yaroslav O. Halchenko
  4. Samuel A. Nastase
ds000233 <p>Functional MRI was used to measure hemodynamic responses while participants viewed brief naturalistic clips of behaving animals under two task contexts. Twelve right-handed adults participated in the study. Functional and structural images were acquired using a 3 T Philips Intera Achieva MRI scanner with a 32-channel phased-array head coil (functional: TR/TE = 2000/35 ms, flip angle = 90&deg;, resolution = 3 mm isotropic; structural: TR/TE = 8.2/3.7 ms, flip angle = 8&deg;, resolution = 0.9375 &times; 0.9375 &times; 1.0 mm voxels). In total, stimuli comprised 40 unique 2 s video clips and their horizontally flipped counterparts for 80 visually unique clips. Ten unique runs were created and run order was counterbalanced across participants. Stimuli were presented in pseudorandom order and each of the 80 stimuli occurred once per run. Each event consisted of a 2 s stimulus presentation followed by 2 s fixation. Stimuli were organized into five taxonomic categories (birds, insects, reptiles, primates, and ungulates), and four behavioral categories (eating, fighting, running, and swimming) in a factorial design for 20 total category-level conditions. Participants were instructed to maintain fixation between trials, but freely viewed the video clips. Participants performed two different 1-back category repetition tasks. In half of the runs, participants were instructed to press a button when they noticed a taxonomic category repetition, and in the other half of the runs they were instructed to press the button when they noticed a behavioral category repetition. Repetition events were sparse by design (~4 per run of each type) and participants were instructed to ignore task-irrelevant repetitions.</p> 12 Philips Intera Achieva PDDL
Immaturities in Reward Processing and Its Influence on Inhibitory Control in Adolescence (Ring Reward)
  1. B. Luna
  2. K. Velanova
  3. T. Teslovich
  4. R. Terwilliger
  5. Geier, C. F.
ds000121 <p>The nature of immature reward processing and the influence of rewards on basic elements of cognitive control during adolescence are currently not well understood. Here, during functional magnetic resonance imaging, healthy adolescents and adults performed a modified antisaccade task in which trial-by-trial reward contingencies were manipulated. The use of a novel fast, event- related design enabled developmental differences in brain function underlying temporally distinct stages of reward processing and response inhibition to be assessed.&nbsp;</p> <p>Briefly, our model consisted of 6 orthogonal regressors of interest (reward cue, neutral cue, reward preparation, neutral preparation, reward saccade response, neutral saccade response; &ldquo;correct AS trials only&rdquo;). We also included regressors for reward and neutral error trials (consisting of the entire trial), regressors for baseline, linear, and nonlinear trends, as well as 6 motion parameters included as &ldquo;nuisance&rdquo; regressors. A unique estimated impulse response function (IRF, i.e., hemodynamic response function) for each regressor of interest (reward and neutral cue, preparation, and saccade; &ldquo;correct AS trials only&rdquo;) was determined by a weighted linear sum of 5 sine basis functions multiplied by a data determined least squares&ndash;estimated beta weight. The estimated IRF reflects the estimated BOLD response to a type of stimulus (e.g., the reward cue) after controlling for variations in the BOLD signal due to other regressors. We specified the duration of the estimated response from stimulus onset (time = 0) to 18-s poststimulus onset (13 TR), a sufficient duration for the estimated BOLD response to return to baseline, for each separate epoch of the trial. We made no assumptions about its specific shape beyond using zero as the start point. Several goodness-of-fit statistics were calculated including partial F-statistics for each regressor and t-scores comparing each of the 5 estimated beta weights with zero.</p> <p>&nbsp;Scripts: <a href="https://github.com/LabNeuroCogDevel/openfmri_ring_rew">https://github.com/LabNeuroCogDevel/openfmri_ring_rew</a></p> <p>&nbsp;ScanSheets: <a href="https://docs.google.com/spreadsheets/d/1kzNxuRPnyalaG5K66ADFIavJOYfQl5OXQSmudNwc0Ak/edit?pli=1#gid=896164689">https://docs.google.com/spreadsheets/d/1kzNxuRPnyalaG5K66ADFIavJOYfQl5OX...</a></p> 28 3T Siemens Allegra MRI scanner PDDL
Multiband Multi-Echo Simultaneous ASL/BOLD for task-induced functional MRI
  1. Yang Wang
  2. Andrew S. Nencka
  3. Alexander D. Cohen
ds000254 <p>This study applies a sequence combining pseudo-continuous ASL (pCASL) labeling with a multiband (MB), multi-echo (ME) acquisition for simultaneous BOLD and ASL echo planar imaging (MBME ASL/BOLD) for block-design task-fMRI. A MB-factor of 4 was employed and 4 echoes were collected. Data was acquired during a bilateral finger-tapping task with 40s tap and rest periods. Multi-echo independent component analysis (MEICA) was implemented to automatically denoise the BOLD and ASL signal. This technique led to increased temporal signal-to-noise ratio (tSNR) and sensitivity. Signal characteristics and activation were evaluated using single echo BOLD, combined ME BOLD, combined ME BOLD after MEICA denoising, perfusion-weighted (PW), and perfusion-weighted after MEICA denoising time-series. Our data suggest that the MBME ASL/BOLD sequence can be employed to collect whole-brain task-fMRI with improved data quality for both BOLD and PW time series, thus improving the results of block-design task fMRI.</p> 13 GE MR750 DV25_R01 PDDL
Effects of mouth breathing on hippocampal activity examined by 3T fMRI
  1. Chang-Ki Kang
  2. Chaejoon Cheong
  3. Young-Bo Kim
  4. Yeong-Bae Lee
  5. Nambeom Kim
  6. Chan-A Park
ds000177 <p>We investigated the effects of mouth breathing and typical nasal breathing on brain function, using blood-oxygenation-level-dependent (BOLD) functional magnetic resonance imaging (fMRI).</p> <p>The study consisted of two parts: the first test was a simple contrast between mouth and nasal breathing and the second test involved combined breathing modes, e.g., mouth inspiration and nasal expiration. Eleven healthy participants performed the combined breathing task while undergoing 3T fMRI. In the group-level analysis, contrast images from the nasal or mouth breathing acquired by the participant-level analyses were analyzed using a one-sample t-test. We also performed a region-of-interest analysis comparing signal intensity changes between the breathing modes; the regions were selected using an automated anatomical labeling map. The results demonstrated that BOLD signal in the hippocampus and brainstem decreased significantly during mouth breathing, whereas the signal increased in the central gyrus. Given that the hippocampus participates in cognitive functions such as memory, decreased hippocampal activity may explain the adverse effects of mouth breathing on brain function.&nbsp;</p> <p><strong>In this dataset:&nbsp;</strong>High resolution T1 weighted structural and BOLD contrast fMRI scans.</p> 11 Siemens Verio 3T PDDL
Behavioral interventions for reducing head motion during MRI scans in children
  1. Nico U.F. Dosenbach
  2. Damien A. Fair
  3. Bradley L. Schlaggar
  4. Steven E. Petersen
  5. Joshua S. Shimony
  6. Rachel L. Klein
  7. Eric A. Earl
  8. Lindsey McIntyre
  9. Catherine R. Hoyt
  10. Annie L. Nguyen
  11. Andrew N. Van
  12. Victoria Wesevich
  13. Jacqueline M. Hampton
  14. Jonathan M. Koller
  15. Deanna J. Greene
ds000256 <p>A major limitation to structural and functional MRI (fMRI) scans is their susceptibility to head motion artifacts. Even submillimeter movements can systematically distort functional connectivity, morphometric, and diffusion imaging results. In patient care, sedation is often used to minimize head motion, but it incurs increased costs and risks. In research settings, sedation is typically not an ethical option. Therefore, safe methods that reduce head motion are critical for improving MRI quality, especially in high movement individuals such as children and neuropsychiatric patients. We investigated the effects of (1) viewing movies and (2) receiving real-time visual feedback about head movement in 24 children (5-15 years old). Children completed fMRI scans during which they viewed a fixation cross (i.e., rest) or a cartoon movie clip, and during some of the scans they also received real-time visual feedback about head motion. Head motion was significantly reduced during movie watching compared to rest and when receiving feedback compared to receiving no feedback. However, these results depended largely on age, such that the effects were driven by the younger children. Children older than 10 years showed no significant benefit. We also found that viewing movies significantly altered the functional connectivity of fMRI data, suggesting that fMRI scans during movies cannot be equated to standard resting-state fMRI scans.</p> <p>The implications of these results are twofold:</p> <p>(1) given the reduction in head motion with behavioral interventions, these methods should be tried first for all clinical and structural MRIs in lieu of sedation; and (2) for fMRI research scans, these methods can reduce head motion in certain groups, but investigators must keep in mind the effects on functional MRI data.</p> 24 Siemens Tim Trio 3T MAGNETOM PDDL
Multi-echo Cambridge
  1. Alex Martin
  2. Peter Bandettini
  3. Prantik Kundu
  4. Valerie Voon
  5. Jonathan Power
ds000258 <p>These are the multi-echo fMRI&nbsp;datasets analyzed in Power et al., 2018 to identify and&nbsp;separate multiple kinds of motion-related variance. More information can be found at&nbsp;<a href="http://www.jonathanpower.net/paper-multiecho.html" rel="noreferrer">www.jonathanpower.net/paper-multiecho.html</a>.</p> 89 Siemens Trio 3T with 32-channel head coil PDDL
Olfactory dysfunction and functional connectivity changes in cognitively normal Parkinson’s disease
  1. Gen Sobue
  2. Masahisa Katsuno
  3. Daisuke Mori
  4. Satoshi Maesawa
  5. Mizuki Ito
  6. Tatsuya Hattori
  7. Michihito Masuda
  8. Yasutaka Kato
  9. Rei Ogura
  10. Kazunori Imai
  11. Reiko Ohdake
  12. Yasuhiro Tanaka
  13. Takashi Tsuboi
  14. Kazuhiro Hara
  15. Epifanio Bagarinao
  16. Kazuya Kawabata
  17. Hirohisa Watanabe
  18. Noritaka Yoneyama
ds000245 <p>In this study, we investigated brain atrophic changes and functional connectivity alterations in Parkinson&rsquo;s disease patients with severe hyposmia, patients with no/mild hyposmia, and healthy controls. All patients were assessed using Odor Stick Identification Test for the Japanese (OSIT-J) and Addenbroke&rsquo;s Cognitive Examination-Revised (ACE-R) for their odor-identification performance and general cognitive function, respectively. We used resting state functional magnetic resonance imaging to evaluate functional connectivity.</p> 45 Siemens Magnetom Verio 3T scanner CC0